The VARK Learning Theory


VARK is an acronym that stands for visual, audial/aural, read/write, and kinesthetic (Fleming & Mills, 1992; Fleming & Baume (2007). The VARK Learning Style Inventory categorizes students’ into one of these four categories based on how they prefer to receive and deliver information (Lang, 2004). Students who are capable of using more than one learning style equally well are categorized as multi-modal learners (Fleming & Mills, 1992). The VARK Learning Style Questionnaire consists of 16 questions and the highest score received in each category determines a student’s learning style.
According to Nilson (2010) the VARK was developed by Fleming and Mills as a framework that reflects the preferred physical sense of learners during intake and putting out information. The VARK model is an expansion of the VAK model, however, VARK further differentiate the visual category into graphical and textual or visual and read/write learners (Murphy, Gray, Straja & Bogert , 2004). The VARK was the first model to systematically use a series of question with help sheets for students, teachers, and employers in order to classify individuals’ preferred way of taking in or giving out information (Fleming & Baume, 2006). The four categories of The VARK Learning Style Inventory are summarized in Table 2.
According to Fleming (2006) and Fleming and Baume (2007) and Drago and Wagner (2004) visual learners prefer to use materials such as charts, graphs, and other symbols to take in and give out information. For these learners, sight is very important especially when taking information in and when organizing ideas. They tend to use colors and highlighters when processing information and the use of diagrams, drawing, and/or recall through pictures to reinforce information and idea intake is recommended. The read and write learners prefer to learn from printed textual learning materials. They tend to use lists, headings, dictionaries, glossaries, definitions, handouts, textbooks, and lecture notes during taking in and giving out information or ideas (Fleming, 2006). Aural leaners on the other hand, prefer to learn through spoken words lessons, talking, debate, and discussions. They tend to understand more when information is explained to them. They learn best through lectures, tutorials, debates, and discussions (Fleming, 2006; Tennent, Becker & Keho, 2005). Kinesthetic learners prefer to learn through direct practice, hands-on activities, and learning by doing (Fleming, 2006). These learners are commonly referred to as “hands on learners”. They learn best through activities such as field trips, tours, field immersion experiences, apprenticeship and activities where they can engage all senses when taking in and giving out ideas or information (Ramayah, Sivanandan, Nasrijal, Letchumanan & Leog (2009). Finally, multimodal learners are students whole learning is based on more than one style. These learners take longer to gather and process information but tend to have a deeper and broader understanding of the information presented (Fleming, 2006). Multimodal learners can be further classified into bi model (VR, VK, AR, AK, AV, KR), tri model (VAK, VAR, VRK, and ARK) and quad model (VARK).
Literature Review of Studies that Used the VARK Questionnaire to Identify Learning Styles
French, Cosgriff, and Brown (2007) examined the learning styles of 120 occupational therapy students at La Trobe University using the VARK questionnaire. Of the 120 students, 33% were kinesthetic learners, 18.1% were quadmodal (where visual or aural learners were the majority, followed by bimodal, and tri-modal was the least learning style of preference for the occupational therapy students. Rathnakar et al. (2014) investigated learning styles of undergraduate medical students using the VARK questionnaire and the influence of sex and academic performance. Four hundred and fifteen second year medical students belonging to two batches participated in the study. Study results showed that 68.7% of participants were multi-modal. The predominant sensory modality was aural (45.5%), followed by kinesthetic with 33.1%. The study also found out that learning preference was not influenced by either sex or prior academic performance. A study by Meehan-Andrews (2009) examined the learning styles of first year health science students to find out the benefits that students received from each teaching strategy. The VARK questionnaire was used in this study to identify student learning style preference. The results indicated that the majority of students were unimodal (54%). Among the unimodal learners, 7% were visual learners, 3% were aural learners, 10% were Read/Write learners and 36% were kinesthetic. The other 46% were multi-modal learners, with 20% bimodal learners, 10% tri-modal, and 16% quadmodal. Finally, a study by Lincoln et al. (2006) investigated the learning styles of adult English as a second language (ESL) students in Northwest Arkansas using the VARK learning style questionnaire. A total of 69 students from 17 different countries participated in the study. The study found out that one third of participants preferred Read/Write learning style. The remaining participants, 17% were multi-modal learners, 4% visual learners, 25% kinesthetic learners, and 20% aural learners.

Validity and Reliability of the VARK learning style questionnaire.
Usability features of the VARK model were investigated by Wehrwein et al (2007). The researchers concluded that the VARK model encourages teachers to be aware of students’ differences before making decisions about what teaching strategies should be used to teach them, supports the idea of matching teaching methods and students preferences, encourages educators to use a variety of teaching strategies and assessment techniques, encourages educators to redesign resources and educational environments, and provides an opportunity for students to talk about their learning style with their teachers. However, the researchers noted that validity and reliability of VARK Questionnaire has not yet been fully verified. A study by Boatman,
Courtney, and Lee (2008) identified a few studies that have evaluated the quality of the VARK Questionnaire. Some of the limitation associated with the VARKs validity and reliability are discussed by Breckler, Joun and Ngo (2008) who proposed that the VARK questionnaire is not a complete inventory as it supplies the users with a simple profile of their sensory learning preferences. Another study by Leite, Svinicki, and Shi (2009) concluded that “researchers using the VARK should proceed with caution because the use and proposed interpretation of VARK scores have not yet received a comprehensive validation” (p. 15).

Reference
Boatman, K., Coatney, R., & Lee, W. (2008). See how they learn: the impact of faculty and student learning styles on student performance in introductory economics. The American Economist, 52(1), 39-48.
Breckler, J., Joun, D. & Ngo, H. (2008). Learning styles of physiology students interested in health professions, Advances in Physiology Education, 33(4), 30-36.
Drago, W., & Wagner, R. (2004). Vark preferred learning styles and online education.
Management Research News, 27(7), 1-13.
Fleming, N. (2005). I am different; not dumb. Modes of presentation (VARK) in the tertiary classroom. In A. Zelmer & L. Zelmer. (Eds). Research and development in the higher education, proceedings of the 1995 annual conference of the higher education and research development society of Australasia (HERDSA), HERDASA, 18 308-313.
Fleming, N. (2006). Teaching and Learning Styles VARK strategies. Christchurch, New Zealand: Neil D. Fleming.
Fleming, D., & Baume, D. (2007). Learning styles again: VARKing up the right tree! Educational Development, SEDA Ltd, 6(4), 4-7.
French, G., Cosgriff, T., & Brown, T. (2007). Learning style preferences of Australian occupation therapy students. Australian Occupational Therapy Journal, 54, 58-65.
Lang, C., Wong, L., & Fraser, J. (2005). Student perceptions of chemistry laboratory learning environments, student—teacher interactions and attitudes in secondary school gifted education in Singapore. Research in Science Education,35, 299-321.
Leite, W. L., Svinicki, M., & Shi, Y. (2010). Attempted validation of the scores of the VARK: Learning style inventory with multitrait-multimethod confirmatory factor analysis models. Educational and Psychological Measurement, 70, 323-339.
Meehan-Andrews, T. (2009). Teaching mode efficiency and learning preferences of first
year nursing students. Nurse Education Today, 29, 24-32.
Murphy, R., Gray, S., Straja, S., & Bogert, M. (2004). Student learning preferences and teaching implications. Journal of Dental Education, 68(8), 859-866.
Nilson, L. (2010). Teaching at its best: a research based resource for college instructors (3rd ed.). San Francisco, CA: Jossy-Bass.
Ramayah, M., Sivanandan, L., Nasrijal, N. H., Letchumanan, T., Leong, L. C. (2009).
Preferred learning style: gender influences of preferred learning style among business students. Journal of US-China Public Administration, 6(4), 65-78.
Rathnakar, P., Ashwin, K., Sheetal, U., Ashok, K., Nandita, S., & Laxminarayana, A. (2014). Assessment of learning styles of undergraduate medical students using the VARK Questionnaire and Influence of sex and academic performance. Advances in Physiology Education, 38(3), 216-220.
Tennent, B., Becker, K., & Kehoe, J. (2005). Technology-enabled delivery and assessment
methods: are we addressing student expectations and learning preferences?.
Proceedings Australian Society for Computers in Learning in Tertiary Education
(ASCILITE) pp 649-659, Brisban, Australia.
Wehrwin, E., Lujan, H., & DiCarlo, S. (2007). Gender differences in learning preferences among undergraduate physiology students. Advances in Physiology Education, 31, 153-175.

Kolb’s Experiential Learning Theory


Kolb’s Learning Style Theory

Kolb’s Learning Style Theory is based on Kolb’s Experiential Learning Theory. Experiential learning theory is influenced by the work of 20th century educational theorists such as John Dewey, Kurt Lewin, Jean Piaget, Wiliam James, Carl Jung, Paulo Freire, Carl Rogers and many others who in one way or the other gave experience a central role in their theories regarding human development (Kolb, 1981, Kolb, 1984, Kolb & Kolb, 2005). Experiential learning theory (ELT) defines learning as “the process whereby knowledge is created through the transformation of experience. Knowledge results from the combination of grasping and transforming experience” (Kolb, 1984, p. 41). The ELT model contains two dialectically related modes of grasping and transforming experience. The dialectically related modes for grasping experience are the Concrete Experience (CE) and Abstract Experience (AE) and the dialectically related modes of transforming experience are the Reflective Observation (RO) and the Active Observation (AE) (Kolb, 1984, Kolb & Kolb, 2005).
Kolb’s experiential learning style theory categorizes the learning cycle into four stages (concrete experience, abstract experience, reflective observation, and active observation), each its own individual learning style preference (Kolb, 1984; Sirin & Guzel, 2006) and summarized in Figure 1. Concrete experience is the process whereby a learner learns through actively experiencing an activity. This is sometimes referred to as learning through hands-on experience. Reflective observation is the process whereby a learner learns through conscious reflection about the activity. Abstract conceptualization on the other hand referrers to the learning process where by a learner learns by being presented with a theory or a model that has to be observed. Finally, active observation referrers to the process whereby the learner learns through testing a theory or a model. According to Kolb and Kolb (2005), experiential learning can be referred to as a “process of constructing knowledge that involves a creative tension among the four learning modes that is responsive to textual demand” (p. 194). Thus in ELT learning follows the learning cycle- the learner experience the phenomenon, reflect on it, think about it, and finally the learner acts on the distilled abstract concepts in a recursive process that is responsive to the situation and the phenomenon being learned (Kolb & Kolb, 2005).
The Kolb learning style theory has identified four types of learners. These are: 1. Divergers, 2. Assimilators, 3. Convergers, and 4. Accommodators. Dorney (2005) described the four types of learners as either exhibiting an only one type of the learning styles (pure) or exhibiting a combination of the four types (extreme cases). Kolb and Kolb (2005) describes divergers as learners having CE and RO as their dominant learning abilities. Learners with this learning style have a greater ability of viewing concrete situations in many diversified points of views. Individuals with the diverging learning style performs better is situations such as brainstorming sessions where ideas are generated. Divergers have interest in people and culture. They tends to be imaginative, emotional, with broad cultural interest and tend to specialize in the arts. During formal learning activities, individuals with diverging learning style prefers to work in groups, listens openly and like to receive personalized feedback. On the other hand, learners with the assimilating learning style have AC and RO as their dominant learning abilities. Assimilators are best at developing concise and logical pattern of information from a wide ranging source of unrelated information. They are less focused on people and culture, however, they are heavily interested in ideas and abstract concepts (Kolb &Kolb, 2005, Rusian, 2005). Assimilators places more value on the soundness of theories rather than practicability. They are a very important group of learners especially in information and science careers. In formal learning activities, assimilators prefers to receive information through reading, lectures, and exploring models. They enjoy having time to think things through.
Learners with a converging learning style have AC and AE as dominant learning abilities. Convergers functions really well at finding practical solutions to ideas and theories. Persons with the converging style prefer to solve technical problems rather than solving social and interpersonal problems. They are an important group of learners in bringing effectiveness in specialists and technology careers. During formal learning activities, convergers prefer to experiment with new ideas through experimentation, simulations, and practical application (Danish et al. 2009, Kolb &Kolb, 2005, Rusian, 2005). Lastly, learners with the accommodating style have CE and AE as their dominant learning abilities. They learn best from hands-on experience. Accomodators rely more heavily on other people for information, analysis, and solving problems rather than relying on themselves or their own technical analysis. They are a very important group of learners especially for bringing effectiveness in action oriented careers such as marketing, teaching, and sales. During formal learning activities, accommodators prefer to work with others to get their work done. They are more action oriented than thinking oriented (Danish et al. 2009, Russian, 2005)
Criticisms of Kolb’s Learning Theory
Despite of the wide use of Kolb’s learning style inventory in education, there are still many criticisms leveled at the theory. Coffield et al. (2004) points out the following flaws: 1) Reliability of the instrument (Learning Style Inventory) is still contested and unresolved, 2) validity of the learning style inventory is still contested and unsettled, (3) there is no evidence that support matching improves academic performance in further education, and lastly, (4) the notion of learning cycles may be problematic as it does not account for all individuals’ information processing preferences. Furthermore, the research on the fluid nature (flexible stable) of learning styles remains both confusing and confused (Robotham, 1999).
A Review of the Studies Conducted Based on the Kolb Learning Theory
Many studies have been conducted based on the Kolb learning style theory. SoyLu –Yilmaz & AkkoyunLu (2009) examined the effect of learning styles on achievement in different learning environments. Thirty nine college level students in an education and instructional technology undergraduate program in Turkey participated in the study. The study used Kolb’s learning style inventory to identify students’ learning styles. For this study, students were categorized into two learning styles: 18 students (53%) were identifies as identified as divergers and 16 students (47%) were identified as assimilators. In other words, students fell into either the diverger group or the assimilator group. The study found no significant difference between instructional strategies in a computer- mediated environment (narrative + music + text + static pictures). Furthermore, In addition, there was no significant change in student achievement when students’ learning style was matched with the instructional strategies (p = .53). Raksasuk (2000) examined the effects of matching learning styles with participatory interaction modes on student achievement among 195 first year students attending a web-based instructional course on library and information science in Thailand. Kolb’s Learning Style Inventory was used to identify students’ learning styles in this study. Of the 195 students, 66 were identified as assimilators, 44 were identified as accommodators, 55 were divergers, and 40 were convergers. Raksasuk found no significant effect in the amount of information learned when instruction was matched to students’ learning styles preference.
Another study by Tulbure (2012), compared two groups of pre-service teachers (with educational sciences (N= 85) and economic sciences major (N = 97) to in order to identify their learning style preferences, the most effective teaching strategies for each learning style and some possible differences between their academic achievement. A total of 182 students participated in the study. The study used Kolb’s learning style inventory to identify student learning styles. Four types of learning styles were identified. For the educational major group, 31% were assimilators (N = 26), 28% were divergers (N = 24), 23% were convergers (N = 20), while only 18% (N = 15) were classified as accommodators (N = 15). For the economic major group, 36% were identified as convergers (N = 36), 25% were identified as assimilators (N = 24), 20% as divergers (N = 19), and 19% as accommodators (N = 18). The results were as follows: Convergers showed statistically significant results with cooperative learning, investigation, and problem solving. Divergers showed statistically significant results when cooperative learning and investigations are used as instructional strategies. Accommodators showed statistically significant results when investigation, debate, and problem solving instructional strategies were used. Assimilators showed statistically significant results when only when problem solving was used.
Bhatti and Bart (2013) examined the effect of learning style on scholastic achievement. One hundred and ninety three undergraduate students studying social science at a Division I Research University participated in the study. Kolb’s learning style inventory was used to identify students’ learning styles. Of the 193 students, 28 were identified as convergent, 49 divergent, 76 assimilators, and 40 accommodator. The major findings of the study was that the dominant learning style was assimilator and that gender and learning styles influenced student achievement. Another study by Smith (2010) investigated the learning style preferences among licensed nurses who were enrolled in a course. The study used Kolb’s learning style inventory to identify the nurses learning styles. The majority of the nurses were identified as accommodators (31%), followed by assimilators and divergers (20%), and the least preferred learning style was convergent (19%).
In summary, Kolb’s learning style theory proposes four types of learners. These are: accommodators, divergers, convergers, and assimilators. Research using this model has identified convergers as the common learning style. However, in my literature review, the discipline seems to determine what the common learning style would be. For example, assimilators dominated the learning style landscape for the social science study, in the nursing field study, accommodators were the majority, and in the economic sciences major group, divergers were the majority. The convergent learner found in this theory is closely aligned to the kinesthetic learner on the VARK theory. However, the Kolb’s learning style inventory is mainly used to identify adults learning styles rather than children as the VARK theory does.

Figure 1. Kolb’s learning experiential model and four learning styles

kolb_learning_styles_diagram_colour
Source: http://www.businessballs.com

References
Bhatti, R., & Bart, W. (2013). On the effect of learning styles on the scholastic achievement. Current Issues in Education, 16(2), 1-6.
Coffield, F., Mosley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles? What research has to say to practice? London, Learning and Skills Development Agency.
Danish, K., & Awan, A. (2009). Learning styles learners and their career choice. Professional Med Journal, 16(2), 162-168.
Kolb. D. (1981). Experiential Learning theory and the learning style inventory: a reply to freedman and stumpf. Academy of Management Review, 6(2), 286-296.
Kolb, D. (1984). Experiential learning theory and the learning style inventory: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall.
Kolb, A., & Kolb, D. (2005). Learning style and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning and Education, 4(2), 193-212.
Raksasuk, Norumol (2000). Effect of learning style and participatory interaction modes on achievement of Thai students involved in web based instruction in library and information science distance education. (Doctoral Dissertation). University of Pittsburg, Pennsylvania.
Robotham, D. (1999). The application of learning theory in higher education teaching. Unpublished article, Wolverhampton Bussiness School, Wolverhampton, UK.
Russian, C. (2005). Preferred learning styles of respiratory care student at Texas University-San Marcos. The Internet Journal of Allied Health Sciences and Practice, 3(4), 1-6.
Sirin, A., & Guzel, A. (2006). The relationship between learning styles and problem solving among college students. Education Sceinces: Theory and Practice, 6(1), 255-264.
SoyLu –Yilmaz, M. & AkkoyunLu, B. (2009). The effect of learning styles on achievement in different learning environments. The Turkish Online Journal of Educational Technology, 8(4): 43-50.
Smith, A. (2010). Learning styles of registered nurses enrolled in an online nursing program. Journal of Professional Nursing, 26(1), 49-53.
Tulbure, C. (2012). Investigating the relationship between teaching strategies and learning styles in higher education. Acta Didactica Napocensia, 5(1): 65-74.

Help find a home and family members for the kids


Blogsphere Family, I am searching for anyone who knew an American man (white) named Dean Edward Erwin and a Tanzanian woman called Rehema Sanga. Mr. Erwin died in Arusha, Tanzania in 2011. He was married to Rehema Sanga. Together, they had three  beautiful children. After the death of Mr. Erwin the mother become mentally ill and no one knows her whereabouts. If you know Dean Edward Erwin family in America or Rehema Sanga’s family, please notify them that the couple’s children were found wondering and begging for food in Chang’ombe, Temeke, Dar Es salaam, Tanzania. Deep down I know there are aunts. auncles, grandmas, and grandpas, both in Tanzania and the United States who could care for, give love, and  provide a home for these children. The children are at Honoratta’s orphanage in Dar Es Salaam. You can reach the orphanage at 011-255- 712-401-818 or 011-255-759-401-818. Please donate food, money or mosquito nets to help the kids or you can just visit them to offer support. Thanks.Help Find A Home for the Kids

A Survey of the Literature on Factors affecting learning Style preferences of the Learner


A Survey of the Literature on Factors affecting learning Style preferences of the Learner

Previous studies have indicated that gender, age, and cultural heritage affects the learners’ learning style (Charlesworth, 2008; De Vita, 2010, Joy & Dunn, 2008; Song & Oh, 2011). Studies have also documented that learning styles are affected by other factors Griggs and Dunn (1998). Thus, factors such as these needs to be considered when identifying learning style preferences of the student as they may influence learning outcomes.

Learning Style and Culture

The influence that culture has on the learning style preference of the learner has been studied and documented in numerous studies. In one study, Song and Oh (2011) conducted a study to examine the learning style preferences of learners who have diverse cultural backgrounds in an online language learning environment. The researchers utilized the Felder and Silverman Learning Style Model to identify students’ learning style preferences. A total of 65 international students enrolled in a Korean language course at a university’s language institute in Seoul, Korea participated in the study. Study participants were culturally diverse representing six cultural clusters: China, Middle East, Europe, Japan, America, and other Asia. The online language course was analyzed using the active/reflective, sensing/intuitive, sequential/global, visual/verbal dimensions of the Felder and Silverman model.  Results indicated significant cultural group differences in the learning style preferences of the learners of Korean language. Song and Oh noted that it is critical to analyze learning styles based on cultural backgrounds of the learners when designing successful online learning courses. In another study, Joy and Kolb (2009) investigated the role that culture plays in way that individuals learn. Experiential learning theory was used as a lens while conducting this study. Kolb’s learning style inventory was utilized to identify students’ learning style preferences. The researchers also used the framework for categorizing cultural differences from the Global Leadership and Organizational Effectiveness (GLOBE) study, to categorize national cultures and individual cultural dimensions. A total 533 respondents residing in seven different nations participated in the study. The findings indicated that the influence of culture on learning styles of the learner was a marginally significant. Furthermore, the researchers also found that individuals tended to have abstract learning style in countries that are high in group collectivism, institutional collectivism, and uncertainty avoidance. The researchers concluded that individuals’ cultural background tend to influence their learning style. Thus, educators need to keep cultural background in mind while designing instruction for their learners.

Charlesworth (2008) examined the relationship between learning style and culture. Honey and Mumford learning style questionnaire was used to identify students’ learning style preferences into reflectors, activists, theorists and pragmatists. Forty one Chinese students, 34 Indonesians students, and 38 French students participated in the study. To ascertain if differences between groups would larger than differences within groups, ANOVA was used. The result indicated statistically significant differences existed between learning styles of the learners classified as activists, reflectors, and pragmatists. Specifically, Indonesian students scored high on the reflector scale, Chinese students scored high on the theorists scale, and French students scored high on the pragmatist scale. Thus, cultural backgrounds affect students’ learning styles and needs to be considered while designing and delivering instruction. In another study, Jia-Ying (2011) explored the influence of cultural background differences on students’ second language/foreign language learning styles. The study focused was to compare these differences between East and Western classroom cultures. A total of 20 graduate students pursuing graduate degrees in the U.S. from China, Japan, Taiwan, and Korea were interviewed for this study.  The evidence from the study revealed that East Asian students adhere to the Confucian traditions and collectivists values. These values affects how students and their teachers interact. Thus, understanding these cultural norms and values is crucial in order for educators to be effective students from different cultures. De Vita (2010) conducted a study to investigate the learning style profiles exhibited by in multi-cultural class of international business management and how cultural influences are reflected on learning style preferences of native and foreign students. The Felder and Solomon Index of learning style was used to identify students’ learning styles. The findings of study suggests that greater variation of learning preferences do exist in multicultural cohorts. Thus, multi-style teaching strategies are recommended to in-order reach all the diverse learners in the course.

In summary, previous studies reveals the influence of culture on learning style preferences of the learner in a multitude of context. Thus, it is advisable to use different type of instructional materials and teaching strategies in order to reach the different type of learners in our multicultural classrooms.

Learning style and age

Age plays a big role on how individuals prefers to receive and give out information. Many studies have shown a relationship between age and learning style preferences of the learner. Cornu (1999) investigated the relationship between learning style, gender, and age amongst students of theology. A questionnaire focusing on contextual examples of global and analytical learning styles was used to identify student learning style preferences. Two batches of students taking theological education participated in the study. The researcher found no significant correlation between learning styles and gender, however, a significant correlation was found between learning style and age. A study by Honingsfeld and Dunn (2003) examined learning style characteristics of 1637 adolescents from five different countries. The Dunn and Dunn learning style inventory was used to identify students learning characteristics. Participants were divided into three groups: 13, 15, 17 years old groups. The evidence indicated a significant difference existed for 16 of the 22 learning style characteristics amongst the three age groups. In another study, Chan (2001) investigated learning styles of 398 gifted and non-gifted Chinese secondary school students. During the study, students were grouped into two groups: 11-13 year olds and 14 – 19 year olds. The result indicated a significant interaction effect between the younger group and learning styles. Chan argued that younger student interacted more with structured activities and games.

In another study, Lincoln et al. (2006) investigated relationship between age and the VARK learning style preferences among student enrolled in English as a Second Language (ESL) courses. A total of 69 students from 17 countries participated in the study. The age groups of participants ranged from late teens to 40s. The result showed a low positive correlation between age and the read/write learning style among all participants (r = 0.197). The results also showed a small negative correlation between age and kinesthetic learning style (r = -0. 32) for male students. Hlawaty (2008) examined the relationship between age and learning style preferences of German students. Hlawaty used the Dunn and Dunn learning style inventory to identify students’ learning styles. The participants were grouped into three main age groups: 13, 15, and 17 year olds. MANOVA result indicated significant differences among all three pair wise comparison of age groups. The researcher noted that each age group has unique learning requirements and concluded that learning demands vary by age of the student. Barun, Schaller, Chambers, and Allisson-Bunnell (2010) investigated the implication of learning style, gender, and age groups for developing online learning activities. The Kolb’s learning style theory was used as a lens in examining responses of online learners to five types of educational activities. Results showed that learning style influences preferences of learning activity. The researchers found a stronger relationship between learning styles and age among adults than among children aged 10- 13 (middle school age).

Despite all these studies indicating a relationship between ages and learning style preferences of the learners, other studies found no existence of a relationship between age and learning styles. Li, Chen, Yang, and Liu (2010) investigated the relationship between age and learning style among students in different nursing programs in Taiwan. The Chinese version of the Myers- Briggs Type Indicator (MBTI) was used to identify students learning style preferences in the four dichotomous of the Jungian theory.  The dichotomous include: extraversion/introversion, sensing/intuition, thinking/feeling, and judging/perceiving.  A total of 331 student participated in the study. The data showed that the most common learning styles were introversion, sensing, thinking, and judging. In addition, the finding also indicated that student age was not significantly related to their learning styles. Seiler (2011) investigated the relationship between age and learning style of adult learners in an online environment. Kolb’s learning style inventory was used to identify students learning styles. A total of 142 students completed Kolb’s learning style survey. The findings indicated a no significant relationship between age and learning styles of learners.  Finally, a study by Adesunloye, Aladesunmi, Henriques-Forsythe and Ivonye (2008) investigated the preferred learning styles of medical student residents and faculty at Morehouse University. The Kolb learning style inventory was used to identify students learning style preferences. A total of 42 participants participated in the study with age ranging from 20 to 59 years old. The study findings showed that there was no relationship between age and learning of the participant.

In summary, the data on the relationship between learning style and age is clearly mix. Some studies in the reviewed literature indicate evidence and support the link between learning style and age, while, other studies shows the lack of evidence to support the link between learning style and age. All in all, classroom instruction needs to take into account learning styles and age differences of the students to maximize learning.

Learning Style and gender/sex.

It is known that males and females learn differently. Numerous learning style preference studies have found a link between gender and preferred styles of learning between the two genders. Raddon (2007) argues that gender is one among many variables considered in learning style studies. Wehrwein, Lujan, and DiCarlo (2007) investigated gender differences in learning style preferences among undergraduate physiology students. The VARK questionnaire was administered to identify undergraduate physiology major learning styles. The students were enrolled in a capstone physiology laboratory at Michigan State University. 86 students participated in the study, however, only 48 students who returned the questionnaire volunteered information their gender information (55.8%). The study found that 54.2% of female and 12.5% of male students preferred a single mode of information presentation. Among female students, 4.2% preferred visual learning style, 0% preferred audial, 16.7% preferred read/write (printed words), and 33.3% preferred hands-on activity to take in and give out information (kinesthetic). Male students had evenly distributed learning style preferences with 4.2% of the students preferring Audial, read/write, and kinesthetic, respectively, while 0% male students preferred the visual mode.

In another study, Dobson (2009) compared student perceived and assessed learning style preferences and examined the relationship between learning styles preferences, sex, and academic performance. A total of 64 students participated in the study, of which 50 were undergraduate students and 14 were graduate students (40 women and 24 men). The researcher found that in the perceived sensory modality data, respondent disproportionally chose visual modality (36%), followed by read/write (28%), kinesthetic (18%) and audial (17%).  In the assessed sensory modality preference, respondents were classified as VARK (37%), followed by read/write (14%), AK (11%), K (8%), VK (6%), ARK (6%), A (5%), VAK (3%), RK (3%), V (2%), AR (2%), and VRK (2%). The researcher also found that there was a nearly significant relationship between sex and perceived sensory modality preference (x2 = 7.18, p = 0.06) and between sex and assessed sensory modality (x2 = 17.36, p = 0.09). However, there was a significant difference relationship between perceived sensory modality preference and academic performance (p = 0.06 by ANOVA).

In another study, Park (1997a) investigated if there were differences between the learning styles of Mexican, Armenia – American, Korean, and Anglo American students. One thousand two hundred eighty three students from 10 high schools in the U.S. participated in the study. The findings from the study indicated that there were differences in learning style preferences between male and female students across the four ethnic groups. Females showed a greater preference to kinesthetic learning style, while males showed a preference to a tactile mode of information presentation. Bernades and Hanna (2009) examined learning style preferences of students in an operations management course. The adult version of the VARK questionnaire was used to identify students learning styles. The researchers found no percent differences between male and female students’ mode of sensory preferences for the unimodal and multimodal learning styles. However, female students significantly preferred multimodal learning styles, whereas, male students significantly preferred a unimodal learning style. Furthermore, Lu and Chiou (2010) conducted a study to examine if gender affects quality of learning through E- leaning by ensuring learning styles of students were satisfactorily met with instructional materials. A total of 353 male and 169 female students from Northern Taiwan University enrolled in online courses participated in the study. Kolb’s learning style inventory was used to identify student learning style preferences. The researchers found a direct and positive relationship between gender and learning style.

In another study, Johnston (1997) examined the learning style preferences of physical education majors and analyzed differences in learning styles. A total of 64 male and 18 female physical education majors participated in the study. The study was conducted at a university in the Southeast of the United States. The Canfield learning style inventory (1988) was used to identify students learning style preferences. The result indicated that both males and females students vary from the norm on learning style preferences. In another study, Honigsfeld and Dunn (2006) investigated gender differences among the learning styles of 1637 adolescents from five countries – Bermuda, Brunei, Hungary, Sweden, and New Zealand. Student learning style preferences were identified using the English or appropriate foreign language (Hungarian, Malay, and Swedish) versions of the learning style inventory (LSI). The result showed significant main effects for gender with medium effect sizes and statistically significant and large effect sizes for country main effects. In addition, there were statistically significant and medium effect sizes for interactions of country by gender.

However, some studies investigating the link between learning styles and gender showed no relationship existed between the two variables. Al-Saud (2013) examined learning style preference of first-year dental students at King Saud University in Riyadh, Saud Arabia: Influence of gender and GPA. A total of 113 students participated in the study, of which 42 were females and 71 were males. The VARK questionnaire was used to identify students learning styles. The researcher found that 59% of the students preferred multi-modes of information presentation. The most common single mode preference was aural (20%), followed by kinesthetic (15.2%). The researcher found out that gender differences was not statistically significant. Urval, Kamath, Ullal, Shenoy, and Udupa (2014) investigated learning styles of undergraduate medical students using the VARK questionnaire and the influence of sex and academic performance. A total of 415 students participated in the study.  The VARK questionnaire was used to identify students learning styles. In addition, demographic data and self-perceived learning style preferences were also collected. The researchers found that the majority of the students had multiple learning style preferences (68.7%). Aural learning style was the predominant single learning style modality (45.5%) followed by kinesthetic at (33.1%). The researchers also found out that gender and previous academic performance did not have any influence of student learning styles preference. Negari and Barghi (2014) explored Iranian EFL learners’ learning style preferences and the role of gender in their learning styles. Ninety EFL learners participated in the study. The participant were from Sistan University, Baluchestan University, and Azad University of Zahedan. The Willing’s learning style questionnaire was used to identify students’ learning style preferences. The result indicated no significant difference between male and female learners’ learning style preferences

In summary, there is a conflict in the published evidence. The research on learning styles preference and gender differences is inconclusive. . In some studies the majority of male students preferred multiple modes of information presentation whereas in other studies female students preferred single mode of information presentation. In some studies a significant difference did exist between how females and male students prefers to take in and give out information. However, in other studies no significant differences between gender and learning styles preferences was found. Thus, educators needs to be aware of the conflicting findings on the research on gender and learning styles. This will help them to design and deliver information to students during instruction in a manner that is compatible to their learning style preference. Broadening and/or using multiple informational presentation styles can help create a more positive and effective environmental for students of all genders to learn. Thus, it is paramount for students and teachers to know student learning styles in order to improve teaching and learning.

References

Adesunloye, B., Aladesunmi, O.,  Henriques-Forsythe, M.,  & Ivonye, C. (2008). The preferred learning styles among residents and faculty members of an internal medicine residency program. Journal of the National Medical Association, 100(2), 172-175.

Al-Saud, M. (2013). Learning style preferences of first-year dental students at King Saud University in Riyadh, Saudi Arabia: Influence of gender and GPA. Journal of Dental Education, 77(10), 1371-1378.

Barun, M., Schaller, D., Chambers, M. & Allison-Bunnell (2010). Implications of learning style, age group, and gender for developing online activities. Visitor Studies, 13(2), 149-152.

Bernades, E., & Hanna, M. (2009). How do management students prefer to learn? Why should we care? International Journal for Scholarship of Teaching and Learning, 3(1), 1-12.

Chan, D. (2001). Learning styles of gifted and non-gifted secondary students in Hong Kong. Gifted Child Quarterly, 45(1), 35-44.

Charlesworth, Z. (2008). Learning styles across cultures: Suggestions for educators. Education & Training, 50(2), 155-127.

Cornu, A. (1999). Learning styles, gender, and age as influential issues amongst Theology student. Journal of Beliefs and values: Studies in Religion and Education, 20(1), 110-114.

De Vita, G. (2010). Learning style, culture, and inclusive instruction in the multicultural classroom: A business and management perspective. Innovations in Education and Teaching International, 38(2), 165-174.

Dobson, J. (2009). Learning preferences and course performance in an undergraduate physiology class. Journal of Advances in Physiology Education, 33, 308-314.

Johnston, B. (1997). Learning style preferences of physical education majors. Physical Educator. 54, 31-34.

Hlawaty, H. (2008). A comparative analysis of learning styles of German adolescents by age, gender, and academic achievement level. European Education, 40(4), 23-25.

Honingsfeld, A., & Dunn, R. (2003). High school male and female learning similarities and differences diverse nations. The Journal of Education Research, 96(4), 195-206.

Jia-Ying, L. (2011). English learning styles of East Asian Countries: A focus on reading strategies. International Education Studies, 4(2), 74-81.

Joy, S., & Kolb, D. (2009). Are there cultural differences in learning styles? International Journal of Intercultural Relations, 33(2), 69-85.

Li, Y., Chen, H., Yang, B., & Liu, C. (2010). An exploratory study of the relationship between age and learning styles among nursing students in different nursing programs in Taiwan.  Nursing Education Today, 31(1), 18-23.

Lincoln, F., & Rademacher, B. (2006). Learning styles of ESL in community colleges. Community Journal of Research and Practice, 30(5), 485-500.

Lu, H., & Chiou, M.  (2010). The impact of individual differences on e-learning system satisfaction: A contingency approach. British Journal of Education Technology, 41(2), 307-323.

Negari., G., & Barghi., E. (2014). An exploration of Iranian EFL learners’ learning style preferences. Modern Journal of Language Teaching Methods. 4(2), 17-24.

Park, C. (1997a). Learning style preferences of Korea, Mexican, Armenian-American, and Anglo students in secondary schools. NASSP Bulletin, 81, 103-111.

Raddon, A. (2007). Distance learners jugging home, work, and study. In P, Cotterill., S, Jackson., G, Letherby. (Eds.). Challenges and Negotiations for women in higher education (pp. 159-181). Dordrecht: The Netherlands: Springer.

Seiler, D. (2011). Age and learning styles of adult learners. The Journal of Human Resource and Adult Learning, 7, 133-138.

Song, D., & Oh, E. (2011). Learning styles based on the different cultural backgrounds of the KFL learners in online learning. Multi-media Assisted Language Learning, 13(3), 133-154.

Urval, R., Kamath, A., Ullal, S., Shenoy, A., Shenoy, N., & Udupa, L. (2014). Assessment of learning styles of undergraduate medical students using the VARK questionnaire and the influence of sex and academic performance. Journal of Advances in Physiology Education, 38(3), 216-220.

Wehrwein, E., Lujan, H., & DiCarlo, S. (2007). Gender differences in learning style preferences among undergraduate physiology student. Journal of Advances in Physiology Education, 31, 153-175.

Facts About Albino Killings in Tanzania: Share Widely.


By Evans Bukuku,

Fact: There are people willing to pay up to Tsh 100 million for body parts of people with Albinism

Fact: There’s a spike in killings of people living with Albinism during political elections (both in Tanzania & neighboring countries).

Fact: The body of 1 year old Yohana Bahati was found just yesterday with legs and arms missing. She had been taken from her mother’s arms by force. Her mother is fighting for her life in hospital as I type. (I have been informed by the Executive Director of Under The Same Son that it does not look good).

Fact: It is election season in Tanzania. This killing will not end here. . . unless me and you do something and/or say something about this.

Myth: As an individual you can do nothing about the situation.

Note: We Can All Do Something to Stop Albino Killings in Tanzania

Stop Albino Killings in Tanzania. Spread the Word!

Stop Albino Killings in Tanzania. Spread the Word!

A Case Study: A Juvenile offender’s Account of His Experiences at Home, the Streets, and at a Metro Atlanta High School in Georgia.


A Case Study: A Juvenile offender’s Account of His Experiences at Home, the Streets, and at a Metro Atlanta High School in Georgia

Introduction

In 2011, there were 34946 juvenile offenders in the state of Georgia (Department of Juvenile Justice, 2013). Of the 34946 offenders, 24319 were males and 10627 were females. The racial distribution of juvenile offenders in the state of Georgia in 2013 was 13434 whites, 18788 blacks, 1983 Hispanics, and 741 other races (Georgia Department of Juvenile Justice, 2013). According to Simones and Stones (2012) the state of Georgia classifies juvenile offenses into two main categories: status offenders and juvenile delinquency (Simones & Stones, 2012). By definition, the term status offender refer to youth under the age of 18 engaged in actions that would not be considered crimes if they were perpetrated by adults (Simones & Stones, 2012). These actions includes truancy, curfew violations, running away from home, failure to obey parents, drinking, and smoking (Simones & Stones, 2012). Generally, status offenders poses no harm to others, but, themselves. Juvenile delinquent, however, are youth under the age of 18 engaged in deviant actions that would be considered crimes if committed by adults (Simones & Stones, 2012). Serious deviant acts include drugs use, drug possession, drug trafficking, and vandalism, destruction of property, violent sex and non-violent sex, weapon possession, distribution, and status offenses.

Three year data from the Georgia Department of Juvenile Justice (DJJ) shows a significant decline on the rate of offenses perpetrated by youth in Georgia. There were 40226, 37099, and 34946 juvenile offenses in 2011, 2012, and 2013 respectively (Georgia Department of Juvenile Justice, 2013). In other words, in 2013 there were approximately 6000 less numbers of youth offenses in the state of Georgia than the number of youth offenses in 2011. The reasons for the downward trends are twofold 1) there has been a drop in youth arrest since the introduction of the Juvenile Justice Reform of 2009 that emphasizes only the most serious and violent offenders to be arrested and kept in custody. 2)  the introduction of the Juvenile Reinvestment program whereby youth with misdemeanors and more minor offenses to be diverted into community-based programs aimed at managing and solving core youth problems from dysfunctional families, anger related issues, drug and alcohol abuse, to underdeveloped life skills. Furthermore, the Juvenile Reform Act of 2013 is hoped to strengthen further these core foundations for juvenile justice in Georgia by 1) offering help to youth who are neglected or abused, 2) providing troubled youth with community outreach and services they need, rather than detaining them, and 3) providing security to Georgia residents from high-risk youth offenders and a less tax burden to Georgia residents by detaining only serious and violent youth offenders. Thus, not paying high security costs for low-risk youth offenders (Georgia Department of Juvenile Justice, 2013). The cost of housing one juvenile offender in Georgia is estimated to be an upward of $70,000 per year.

Study Rationale

 

As mentioned earlier, the rate of juvenile offenses are falling each year. However, the difficulties that juvenile offenders face while transitioning from juvenile detentions to local school is still a huge obstacle to their learning. This research will identify personal experiences that juvenile offenders face when at home, in the streets, and when returning back to school after detention. In addition, the research will also find out the likelihood that a juvenile offender will commit the same or similar offenses in the future. The identified factors will help school administrators, teachers, and parents to create programs at the schools to easy and benefit juvenile offenders’ transition back to school for better learning outcomes.

Literature Review

Root Causes of Juvenile Crimes

Juvenile crime is not just a Georgia problem, it is a countrywide and worldwide problem. The main causes of juvenile crimes differ in different parts of the world (Theodore, 1966; Ruthshonle, 1970; Ragoli & Hewitt, 2006). Most sociologists regard poverty, family structure, family process, dysfunctional families, peer pressure, and substance abuse as the main causes of crime (Ruthshonle, 1970; Ragoli, Hewitt & John, 2006). In the developed world, poverty due to unemployment of the father and unemployed of the mother has being linked to juvenile crimes (Ragoli, Hewitt & John, 2006). However, Poverty does not cause crime. The resentment of poverty in rich society is directly associated with crimes (Ruthshonle, 1970). Resentment of poverty is more likely to develop among the deprived groups in rich societies than among the objectively deprived in poor society (Ragoli, Hewitt & John, 2006).

Several studies have shown there is a relationship between poverty and crime (Sutherland, Donald, & Cressey, 1955, Theodore, 1966, Shaffer & Knudten, 1970; Ragoli, Hewitt & John, 2006). Some studies on the economic status of the criminals have indicated that lower economic groups have more rates of crimes than high economic groups (Selling, 1937; Frank & Status, 1956; Theodore, 1966). In the case of juvenile crimes, poverty, family structure, family processes, dysfunctional families, peer pressure, and youth substance abuse problems are closely related to juvenile crimes (Center on Juvenile and Criminal Justice, 2012)

Theories

            There are many theories that attempt to explain juvenile crimes, however, for this study, two theories will be discussed. The two theories are: the broken home theory and the looking glass-self theory. In this section, I will briefly describe these two theories and criticisms or shortcomings of the theories.

The Broken Home Theory

            Single family homes have been faulted by government and media as the main cause of juvenile crime in America (Center on Juvenile and Criminal Justice, 2012).  The term “broken home” has been operationalize to mean children living in single parents households or any other type of household other than a household in which both biological parents are present ( Ranking, 1983; Geismar & Woods, 1986). Conversely, an intact family refers to a nuclear family in which both biological parents resides in a households with their biological children (Kierkus & Baer, 2002).

Critics of the broken home theory argues that juvenile crime trends does support this theory. Recent juvenile crimes statistics shows that from 1997 to 2012, juvenile crime has declined 33% while single parent households have been increasing a steady rate (Center on Juvenile and Criminal Justice, 2012). In addition, a classical study by Shaw and Mckay (1932) investigated the role of broken homes in juvenile crime and noted the importance of broken homes in juvenile crime has been overstated.  Shaw and Mckay (1932) suggested that prior research regarding delinquents from intact families and delinquents from broken homes failed to control for factors such as age, race, and family situations. Over time, researchers have questioned the broken home theory and that intactness of the family explains all the variables related to juvenile crime. A more recent study by Demuth and Brown (2004) found out that broken homes are associated with juvenile crime, however, they found out also that broken homes are not the only issues related to juvenile crime. The researchers found out that teenagers living with their fathers had much higher rates of juvenile crime than teenagers living in both parent households. Demuth and Brown concluded that the lack of parental involvement and supervision between the parents and the teenager are factors that influence juvenile crime.

In summary, these two studies shows that family structure alone has little effect on juvenile crime. Family factors such as parental involvement, attachment, and supervision are better explanations of juvenile crime and juvenile deviant behavior. Now I turn to the looking glass-self theory and its influence on juvenile crime.

The Looking Glass-Self Theory

            The looking glass-self theory was put forth by Charles Horton Cooley. Retzer defines the looking glass theory as:

The concept of looking glass-self can be broken down into three components: First, we imagine how we appear to others. Second, we imagine what their judgment of that appearance must be. Three, we develop some self-feeling, such as pride or mortification, as a result of our imagining others’ judgment (Ritzer, 2008).

The looking glass-self theory is similar to the labelling theory. However, the looking glass-self theory is an internalization of what we perceive others think of us. Our personal belief changes to match what others think or say. For example if someone sees you as a smart and intelligent person, you are likely to see yourself as smart and intelligent person. In the same token, if someone sees you as a delinquent person, you are more likely to see yourself as a delinquent. The internalization becomes more evident if it comes from someone of authority or power. Self-concept is shaped by these interactions. Thus, schools, homes, police officers, bosses at work plays a big role in shaping self-concepts (Ritzer, 2008).

In addition, when looking at juvenile delinquent, it is without a doubt that self-concepts are a result of how powerful others sees and think of them. They internalize formal opinions of being drug addicts and delinquents through formal opinions of friends and family. Furthermore, when their parents are disappointed and disgusted of them, they also feel disappointed and disgusted of themselves. Their self-concept is formed by what they think others will say or think about them. This is more predominant when the opinion comes from a person in a position of power (Ritzer, 2008).

The Current Case Study Focus

            The current case study attempted to answer the question “How Juvenile delinquent students’ experiences back in schools after incarceration can help schools develop better mechanism to help them succeed in schools and home life?”. Specifically, this case study through a one-on-one interview collected information from a juvenile delinquent student regarding: 1) age, 2) Race, 3) Home Structure, 4) Experiences with Parents, 5) Street Life, 6) School experiences after Incarceration, and 7) The Chances for committing the same or similar crimes in the future.

 

Methodology

While examining a possible method to capture juvenile delinquents’ experience returning back to school after incarceration, a single instrumental case study emerged slowly but surely as the best method for capturing an in-depth understanding of this experience. Specifically, the case study attempted to capture juvenile delinquents’ experience and their home structure, experiences with their parents, street life, school experiences after incarceration, and the likelihood that they will commit same or similar types of crimes in the future (Starke, 1995; Yin, 2009). In a single instrumental case study the researcher “focuses on an issue or concern and then, select one bounded case to illustrate the issue” (Creswell, 2007; p. 99). The current study is bounded within the same school environment and it provides an in-depth understanding of the issues impacting juvenile delinquent students at home, in the street, and in their schools after incarceration. The study also provide an understanding of the background information of the student participant in this study.

Consistent with the case study design, the researcher identified a juvenile participant who had recently been incarcerated for the interview. The researcher interviewed the juvenile participant using a semi-structured interview protocol that consisted of five areas and questions:  Biographical information and Race–what is your date of birth? What is your race? What are your current charges? Home life: what type of household do you reside in? How well do you get along with your mother? How well do you get along with your father? How well do you do in school? Have you ever hold a job? Street life: Do you party a lot? Do you get high a lot? What kind of stuff do you take? Do you belong to any gang? School life after detention: How does the school help you to adjust back to school? Does the school give you a mentor to help you with the missed work? How difficulty was it for you to catch up back in your learning? What do you think the school should provide or do for student with similar circumstance as yours? Future crime self-prediction: Do you think you will commit same or similar crimes in the future? What are you doing to prevent future incarceration?

Procedure

            Permission was sought from the student participant participating in the study. Data collection took place in the researcher’s own lecture room. Name of the student participant was not disclosed. To further guarantee the privacy of the juvenile involved in this case study, the semi structure survey instrument and the recording of the interview was kept in a secure computer only accessible with a secret password protection that only the research of this study knew.

Data collection included basic biographic information of the juvenile participant (age, sex, and race). Other information included the home structure and whether the participant got along with their mother and father, the specific type of crimes they committed, street life, school experiences after returning from incarceration, and the possibility of committing crimes in the future.

Data Analysis

            The collected data in this case study was analyzed following Yin (2009) suggestions: 1) to focus on a few key issues and not to use those issues for generalizing beyond the case, but, for understanding of the complexity of the case. 2) to identify issues within the case and then looking for common themes within the case and the literature.  The themes that emerged in this case study a presented below.

Results

This section organizes the findings from the interview with a student juvenile offender into the five main question themes: Biographical information and race, home life, street life, school life after incarceration, and self-prediction for committing future crimes.

Biographical information and race

Mr. K.C. was born in October 7th, 1997. He of mixed races. His father is an African American and his mother is Mexican. His present charges includes concealing a weapon, distributing weapons, among many other serious charges.  He just got back to the community school from incarceration in the last 6 weeks.

Home life

Mr. K.C. lives with him mom in an apartment complex. His mom has four other children. He does not really know his biological father. His biological father abandoned his mother when he was toddler. Thus, he does not have any recollection of his father. Mr. K.C. gets along well with his mother. They talk a lot. He feels like he has a very tight relationship and bond with his mother. He has lived without a “father figure” in his life until recently when his mother started dating another man. This man is now his step-father. He did not get along very with his step-father in the beginning of their relationship. However, now they do get along very well and he helps him understand the consequences of his choices. Mr. K.C. has never held a stable job. He has worked briefly in construction, landscaping, and under the counter jobs. Thus, he has worked shortly and mostly in manual labor type of jobs.

Street life

Mr. K.C. does not party a lot. He mostly hustles. According to Mr. K.C. hustling means “I sell something that people need or take what you got”. However, Mr. K.C. does get high a lot. He smokes weed, sometimes he takes pills, although, he is not a big fun of pills. He occasionally drinks and sometimes does cocaine. Mr. K.C. is affiliated with the bloods.

School life after incarceration

The local county school system tried to prevent Mr. K.C. from coming back into the school because of the serious nature of the charges he had and still has with the juvenile court. He hired a lawyer who advocated for him to come back to school. It took the lawyer about a month for that process to be completed. Now he is back in school like any other regular student. His grades are decent and he feels like he is doing well academically and socially. When he came back to school, he was just handed his missing work and told here is your work. He felt like the teachers throw the work on his face without any type of guidance or help for him to complete it. The school administration did not help either. There was no mentorship from the school to help him complete the missed assignments. He, however, was given a mentor with the state who helped him to deal with his anger, drug use, and other life related problems. The mentor was not academically qualified to help him with school work. She was there just to check on him on a weekly basis, to help him stay out of trouble that could land him back to juvenile detention.

Mr. K.C. accoutered a lot of difficulties when he came back to school after being incarcerated. He had a reputation of “he just is going to do bad”. He felt like the teachers looked down on him. He had to convince himself that he was capable of doing the school work. Even though he had a lot of negativity around him, it did not hold him back. His suggestion for people finding themselves in his shoes is to just keep themselves positive. The school could create a mentorship pool just targeting people like him to offer academic help and socialize with them to make them feel they are welcome at the school.

Self-prediction to commit future crimes

Mr. K.C. thought that the best way to avoid future incarceration is to try his best to stay out of trouble. He hoped he will be able to do just that. According to Mr. K.C. “it is kinda hard in todays’ society to stay out of trouble complete, you know”. He tried to find a job in various places, however, because of his type of charges he has not been called back for an interview or anything. Mr. K.C. also said “everybody needs to get money and without a job, I see myself getting in trouble again”.

Discussion and Conclusion

In this section, I first analyze the data, then, I present the conclusions of the study, and finally, I present my recommendations for future research.

Living in single family household

A number of research has been conducted to determine the relationship between single family homes and juvenile crime (Ranking, 1983; Geismar & Woods, 1986). Broken homes are associated with juvenile crime (Dethmuth & Brown, 2004), however, the broken homes theory alone does not explain juvenile crimes completely (Shaw & Mckay, 1932). In this case study lived for the past his life in broken home. This could partly explain the relationship between his engagements in juvenile crimes. However, there are myriads of other factors such as the lack of bonding between the participant in this study and his biological father, the ineffective or lack of supervision from the biological mother. The biological mother has five children and because of lack of proper education, she works many hours to provide for her children. Thus, she always not in the house and the juvenile in this case study had to learn to be a grown and supervise other kids in the house at an early age. All these factors combined could help explain the association between him and his tendency to commit juvenile crimes.

Smoking pot and Drug Use

The literature on juvenile crimes indicates that there is an association between smoking weed, doing heavy drugs, and committing juvenile crimes (Committee on Substance Abuse and Committee on Adolescence, 2004). In this case study the juvenile participant smokes weed and is engaged in drug abuse. He was introduced to marijuana and other heavy drugs such as pills, cocaine, and other forms of injectable substances from an early age. This exposure to drugs and marijuana could help explain the participant’s tendency to commit juvenile crimes. The use of marijuana and drugs causes juvenile and adults users to lose the ability to think clearly which then leads to poor decisions making (Committee on Substance Abuse and Committee on Adolescence, 2004). In addition, sustaining a drug abuse habit requires money. Since, many youth abusers do not have jobs and money, they tend to commit crimes to generate income to support their habits.

Back to school difficulties after incarceration

Based on my interview with the juvenile participant in this case study, there several problems or difficulties that juvenile offenders face when they return back to a community school after incarceration. I will discuss two major difficulties they face:  first, lack of support and two, being looked down upon. Once juvenile offenders are cleared to come back to school there are no support systems within the school to help them with their transition. It is a common practice that once a juvenile offender reports back to class is given the work that he or she has missed for the time that he or she was incarcerated. However, there are no academic support groups to help them understand the information. The juvenile offender in this case study described this experience as “the teachers just throw the work on your face” and “you just have to do it with no help whatsoever”.

In addition, the juvenile offender in this case study expressed his frustrations with what he calls as “being looked down upon” phenomenon. Once a juvenile offender comes back to school he or she has to overcome the negativity related to being incarcerated. According to the juvenile offender is this case study, “teachers, administrators, and students looks down on you with the perception that you are just going to cause more problems to them”.  The looking glass-self theory applies directly here. It is without a doubt that juvenile offenders’ self-concepts are a result of how powerful others sees and think of them. They internalize formal opinions of being drug addicts and delinquents through formal opinions of teachers, administrators, friends and family. The way we treat juvenile offenders once they come back to school could have a serious effect on their self-concept and how they see themselves.

The state does provide a mentor for the student, however. The state mentor is there just to help the juvenile offender to deal with their drug abuse problems and issues related to their incarceration. Often times, the state mentor does not know how to tutor juvenile offenders in subjects related matters. Thus, there is a great need for schools to develop plans to meet the needs of juvenile offenders (mentally, socially, and academically) for them to be successful with their learning.

The likelihood for committing future crimes

In this case study, the juvenile offender hoped that the incarceration incident that happened to him will be a thing of the past. He was hopeful for the future. However, he cautioned that because of his incarceration and the serious nature of the charges against him it may not be easy for him to find a job post high school and then lead to him committing crimes in the future.  According to him “in today’s world everybody has to have money to survive, if I cannot find a job, I will have to do……you know what I mean, to make money”.  Therefore, a future without crime, is not certain for him.

Recommendations for future research

This case study was centered on a single research participants’ personal experiences at home, the street, and the school after incarceration.  Four themes emerged from the interview and discussions with research participants. The emerged themes include: (1) single family household, (2) smoking pot and drug use, (3) back to school difficulties after incarceration, (4) the likelihood for future crimes. As discussed in the study results and discussion, these themes have direct implications for the effectiveness of programs to help juvenile offenders transition back to school and learning. In order to validate the results from this study, additional research with juvenile offenders from different settings is needed.  For example, studies with juvenile offenders from middle school or other high school setting or from urban high schools and suburban high schools would be desirable. In addition, the questions used to capture juvenile offenders’ personal experiences at home, in the streets, and at schools after incarceration in this study were not very focused. Therefore, studies with more focused questions on this matter are needed to capture the essence of these experiences. Finally, I realize that one’s cultural background influences one’s experiences.  My background, cultural experiences, and world view may have affected the way I analyzed the data. Therefore, research done by people with different cultural and background experiences are warranted.

Reference

Committee on Substance Abuse and Committee on Adolescence. “Legalization of Marijuana: Potential Impact on Youth.” Pediatrics Vol. 113, No. 6 (June 6, 2004): 1825-1826.

Creswell, J.W. (2013). Quantitative inquiry and research design: Choosing among five approaches (3rd Ed.), Thousand Oaks, CA: Sage Publications, Inc.

Dethmus, S., & Brown, S. (2004). Family structure, family processes, and adolescent delinquency: The significance of parental absence versus parental gender. Journal of Research in Crime and Delinquency, 41(1), 58-81.

Frank, A., & Status, H. (1956). The criminal, the judge, and the public. New York, NY: Free Press.

Geismar, L. L., & Woods, K. M. (1986). Family and delinquency: Resocializing the youth offender. New York, NY: Human Sciences Press.

Georgia Department of Juvenile Justice (2014). Statewide statistics. Accessed: http://www.djj.state.ga.us/ResourceLibrary/rptstatDescriptive.asp?type=State

Kierkus, C., & Baer, D. (2002). A social control explanation of the relationship between family structure and delinquent behavior. Canadian Journal of Criminology, 44(4), 225-258.

Ragoli, R., Hewitt, M., & John, O. (2006). Delinquency in society (6th ed.). New York, NY: Randam House.

Runshonle, C. (1970). Juvenile delinquency. In R.D. Knudten & S, Schafer (Eds.): A reader: Offences primarily injurious to others. New York, NY: Randam House

Schafer, S., & Knudten, R. (1970). The nature of delinquency: Juvenile delinquency an introduction. Philadelphia, New York: J.B. Lippincott Company.

Sellin, T. (1937). Culture, conflict, and crime: Research memorandum of crime in depression. New York, NY: Randam House.

Shaw, C. R., & Mckay, H. D. (1932). Are broken homes a causative factor in juvenile delinquency? Social Forces, 10, 514-524.

Starke, H. F. (2010). The arts of case study research. Thousand Oaks, CA: Sage.

Sutherland, E., Donald, H., & Cressey, R. (1955). Principals of criminology (5th ed.). Chicago, Philadelphia, New York: J.B. Lippincott Company.

Theodore, F. (1966). Typologies of delinquencies: A social typology of delinquency a critical analysis. New York, NY: Randam House.

Yin, Y. K. (2009). Case study research: Design and method (4th ed.). Thousand Oaks, CA: Sage.

Diversity Issues in American Schools: An Overview


Diversity Issues in American Schools: A Brief Overview

America has been a diverse country since its inception (Banks & Banks, 2001). Many groups of people have migrated to the U.S in search of religious freedom, economic opportunity, and a better life for themselves and their children (Millet, 2000). Thus, America is often referred to as a country of immigrants. In the beginning, most immigrants came to America to stay for good. These groups of immigrants eliminated all ties with their countries of origin. This created a country of oneness and aided the formation of the melting pot theory. In the melting pot theory the focus is on the outcome, you don’t care about the difference between the members in a society. What is more important is the end results, that is, creating a country of oneness despite all the differences in the ingredients that created it.

However, the turn of the 20th century has seen another big wave of immigrants to the United States. Recent immigrant populations are quite different from the previous ones, however. In that, most of the recent immigrants still hold ties and direct relationship to their countries of origin (Spring, 2001). This phenomenon is aided by advancement in technology. Due to technology, the world has become smaller, hence the analogy “living in a global village”. As a result, the recent immigrant population can be captured better using the salad bowl theory. The salad bowl theory argues that the oneness of America concept fail to capture the true racial, cultural, and ethnic diversity of American. The theory asks us to consider and appreciate the different parts or ingredients that makes up todays America. Things such faith, values, tradition, political views, world views, and value system among the different groups of Americans needs to be appreciated rather than dismissing them all-together.

Addressing Multiculturalism and Diversity in Schools

Schools mirror societies. Because of the increased diversity in the population at large, school systems in America are also experiencing an upsurge in students, educators, and school leaders’ diversity (Banks & Banks, 2001). To help all students from the different ethnic groups, racial groups, cultural groups, economic groups, and social groups learn, a conscious effort is need to embrace multicultural education and diversity in all our schools. This can only be achieved through authentic training regarding diversity and multiculturalism to educators, school administrators, and students. Without a conscious and continued efforts to understand, appreciated, and celebrating the diverse views of others and of ourselves, I am afraid no progress will be made.

Do Leader Keys Address Cultural Competency?

In order to answer the question “Do leader keys training address cultural competency? I interviewed an assistant principal at a school in the Metro Atlanta area. Before the interview, I decided to familiarize myself with the definition of cultural competency. Cultural competency refers to an ability to interact effectively with people of different cultures (Taylor, et al., 1998). Cultural competence comprises four components: (a) awareness of one’s own cultural worldview, (b) attitude towards cultural differences, (c) knowledge of different cultural practices and worldviews, and (d) cross-cultural skills. Developing cultural competence results in an ability to understand, communicate with, and effectively interact with people across cultures (Von Bergen, Soper, & Foster, 2002).

Once I had a firm understanding of the term cultural competency, I decided to develop four questions to direct the interviewing process. The questions I developed are: 1) what does cultural competency mean to you? 2) was cultural competency part of the training you received in your leader keys training? 3) how long was the leader keys training? was it a one shot training or a continuous training? 4) how important is cultural awareness when evaluating educators in a diverse society like ours?

I contacted three assistant principals at two different schools in the Atlanta Metro area. One of the three agreed to meet me at a Starbucks coffee shop for an interview. I sent the interview questions to the interviewee three days prior to our meeting.  The interview responses and my analysis of those responses are included below.

When responding to the question “what does cultural competency mean to you?” the assistant principal described “cultural competency as the ability one has to understand others’ world view. She continued by saying….It is my understanding of others and how they view education and the process of educating students.” While I agree with the assistant principals’ understanding of the term cultural competency, I however, believe that cultural competency is more than understanding other people’s world views. My opinion is that, cultural competency is about understanding your own cultural and world view first and being strong enough not to impose your world view onto others. In addition, it is also important to have the ability to understand, communicate with, and effectively interacting with people from other culture without showing elements of prejudice.

When asked whether cultural competency was part of the leader keys training, the assistant principal flatly said, it wasn’t. According to her, leader keys training takes only one week.  She added, there are refresher meeting and follow-ups during the course of the year. She added that all leaders do receive a cultural competency training, however, in other types of mandatory district training such as the sexual abuse training, computer competency training, and others. I feel as though cultural competency training should be a part and parcel of the overall leader keys training. Currently, the educator population in the U.S is increasing becoming diverse. It is becoming an amalgam of different cultural and world views. For a leader to be effective at communicating, interacting, and evaluating a diverse workforce of educators, cultural competency should be a mandatory part of the leader keys training in my views.

Lastly, while addressing the question “how important is cultural awareness when evaluating educators in a diverse society like ours?” The administrator did not think that this was important.  She argued that best teaching practices are the same across cultures. According to her, culture has little to do with best practices. Therefore, when she is evaluating teachers; background, culture, and world view of the educator are irrelevant. Her only interest is to see how the educator is using best practices in curriculum and instruction. In my views, it is sometimes much easier to use the “one size fits all” when it comes to differentiating evaluations. If we ask educators to differentiate instruction, we as leaders should be able to do the same when evaluating educators’ practices. When we fail to do that, it isn’t painting a good picture of our expectations on others. Lamping everyone in one group, makes the work of evaluating educators much easier. On the contrary, I believe culture, world view, and background are important variables and needs to be included in an evaluation. A good understanding of others’ cultures, world views, and backgrounds would make the Teacher Keys Evaluation System (TKES) a better evaluation instrument overall.

Classroom and Online Discussions

            During classroom and online discussions, I was struck by the semblance of views held by some school administrators on cultural competence and multicultural appreciation in schools. For example, in an interview between my classmate Kimberly and her principal. She asked the principal “How does she approach the issue of diversity when hiring faculty at her school”. The answer the principal provided was similar to answer I received in my interview with an assistant principle when I asked “Does she employ cultural competency approaches when evaluating educators?” They all believe that “the one size fits all” approach is the way to go. In my views, some school administrators still hold the views that America is a melting pot country rather than the views that American is a bowl of salad where by individual culture, world views, and values are respected and celebrated in both action and deeds. We celebrate the diversity among us just when it is convenient, however, when it comes to work and education, we hold the assumptions that everyone is one and the same. Aren’t we all Americans after all?

Conclusion

In my capacity as an instructional and curriculum leader, I will work hard to influence those around me on better ways to provide professional development for teachers and administrators that incorporates cultural competency. I feel like the current model of one size fits all is not aligned with the diversity of students, educators, administrators, and families in our schools. I will advocate for authentic diverse professional development training that raises the awareness of our own biases of our multicultural society. I believe that with the amount of knowledge I have acquired in the past two years in this program, I will be able to influence the design and development of training materials and training educators and administers regarding diversity and multicultural issues in our schools. I see myself growing further as an educational leader on these issues. I believe through authentic advocacy, my voice will amplify these issues especially through the mentorship I provide to new educators, and through multicultural and diversity training in the district and hopefully, the country at large.

References

Anderson, G. L. (2009). Advocacy leadership: Towards a post-reform agenda in education. New York, NY: Routledge.

Banks, J.A. & Banks, C.A.M. (2001). Multicultural Education: Issues and Perspectives (4th ed.). New York: John Wiley & Sons, Inc.

Spring, J. (2001). The politics of American education. New York, NY: Taylor & Francis.

Taylor, T., et al. (1998). Training and Technical Assistance Manual for Culturally Competent Services and Systems: Implications for Children with Special Health Care Needs. National Center for Cultural Competence, Georgetown University Child Development Center.

Von Bergen, Soper, & Foster, (2002). Unintended negative effects of diversity management. Journal of Public Personnel Management, 31(2), 239-251.

Do Leader Keys Address Cultural Competency?


Do Leader Keys Address Cultural Competency?

In order to find information to answer the question of whether or not leader keys training address cultural competency, I interviewed an assistant principal at a school. Before the interview, I decided to familiarize myself with the definition of cultural competency. Cultural competency refers to an ability to interact effectively with people of different cultures (Taylor, 1996). Cultural competence comprises four components: (a) awareness of one’s own cultural worldview, (b) attitude towards cultural differences, (c) knowledge of different cultural practices and worldviews, and (d) cross-cultural skills. Developing cultural competence results in an ability to understand, communicate with, and effectively interact with people across cultures (Von Bergen, Soper, & Foster, 2002).

Once I had a firm understanding of the term cultural competency, I decided to develop four questions to direct the interviewing process. The questions I developed are: 1) what does cultural competency mean to you? 2) was cultural competency part of the training you received in your leader keys training? 3) how long was the leader keys training? was it a one shot training or a continuous training? 4) how important is cultural awareness when evaluating educators in a diverse society like ours?

I contacted three assistant principals at two different schools in the Atlanta Metro area. One of the three agreed to meet me at a Starbucks coffee shop for an interview. I sent the interview questions to the interviewee three days prior to our meeting.  The interview responses and my analysis of those responses are included below.

When responding to the question “what does cultural competency mean to you?” the assistant principal described “cultural competency as the ability one has to understand others’ world view. She continued by saying….It is my understanding of others and how they view education and the process of educating students.” While I agree with the assistant principals’ understanding of the term cultural competency, I however, believe that cultural competency is more than understanding other people’s world views. My opinion is that, cultural competency is about understanding your own cultural and world view first and being strong enough not to impose your world view onto others. In addition, it is also important to have the ability to understand, communicate with, and effectively interacting with people from other culture without showing elements of prejudice.

When asked whether cultural competency was part of the leader keys training, the assistant principal flatly said, it wasn’t. According to her, leader keys training takes only one week.  She added, there are refresher meeting and follow-ups during the course of the year. She added that all leaders do receive a cultural competency training, however, in other types of mandatory district training such as the sexual abuse training, computer competency training, and others. I feel as though cultural competency training should be a part and parcel of the overall leader keys training. Currently, the educator population in the U.S is increasing becoming diverse. It is becoming an amalgam of different cultural and world views. For a leader to be effective at communicating, interacting, and evaluating a diverse workforce of educators, cultural competency should be a mandatory part of the leader keys training in my views.

Lastly, while addressing the question “how important is cultural awareness when evaluating educators in a diverse society like ours?” The administrator did not think that this was important.  She argued that best teaching practices are the same across cultures. According to her, culture has little to do with best practices. Therefore, when she is evaluating teachers; background, culture, and world view of the educator are irrelevant. Her only interest is to see how the educator is using best practices in curriculum and instruction. In my views, it is sometimes much easier to use the “one size fits all” when it comes to differentiating evaluations. If we ask educators to differentiate instruction, we as leaders should be able to do the same when evaluating educators’ practices. When we fail to do that, it isn’t painting a good picture of our expectations on others. Lamping everyone in one group, makes the work of evaluating educators much easier. On the contrary, I believe culture, world view, and background are important variables and needs to be included in an evaluation. A good understanding of others’ cultures, world views, and backgrounds would make the Teacher Keys Evaluation System (TKES) a better evaluation instrument overall.

Micro Leadership Issues: K-12 Americana


In the past three weeks, we have been discussing six K-12 major educational issues related to instructional leadership at the micro level. The issues we discussed were: Principal and Teacher Opinions of walkthroughs, Teacher Professional Development, Administrators Training for TKES/LKES for walkthroughs, The Process of Recruiting Principals, The Number of Males vs Female Principals, and Teachers Opinions Regarding Professional Learning. In this reflection, I will briefly touch on three of these issues. In my reflection, I will highlight issues that stood out to me personally during our discussions. I will also discuss how I see these issue impacting me in my capacity as an instructional leader. Furthermore, I will offer my observations and suggestions on how I may grow as an instructional leader while tackling this issue.

American schools have seen a major shift from its focus on student learning to a focus on teacher evaluation and high stakes student testing after the release of the A Nation At Risk Report in 1983 (Anderson, 2009). Among other things, the release of this report has contributed to the ever-growing assertion that American schools are failing.  The failing schools narrative has led to various school reform efforts at the school, the local district, the state, and at the national levels (Lavitch, 2009). Some of the recent school reform effort includes the No Child Left Behind Act (NCLB) of 2001 with its emphasis on testing and school choice, the Race to the Top with its emphasis on tying student testing to teacher evaluation, and the adoption of the Common Core Standards.

The NCLB introduced most of the data driven accountability and management we are now experiencing all the way down the education ecosystem to the school level. The NCLB legislation “sought to close the achievement gap between the rich and the poor students by creating common curriculum standards, closing the so called failing schools, and introducing the public reporting of student test scores” (Spring, 2011, p 36). However, prior to the NCBL legislation, educators had some autonomy to choose instruction strategies for their classroom, to create meaningful lesson plans, and to design appropriate evaluations to test student knowledge and understanding. While teacher accountability may have been difficult to measure under the system prior to NCBL, I now feel, like Spring, that the current model of teaching consisting of    “scripted lessons created by outside agency” and that teachers are increasingly forced to teach to the requirements of standardized tests is harmful to education and to the children of America receiving this education.

While discussing the principals and teachers’ opinions of walkthroughs I was struck by the differences in opinions between the two groups. Some teachers, on one hand believes that walkthroughs are an inauthentic exercise. They just “put on a show” during walkthroughs for the purpose of satisfying the evaluators. There is no a genuine interest in the process. Walkthroughs causes teachers to be nervous because walkthroughs are tied to teachers’ contractual obligation. On the other hand, principals feels as though walkthroughs are necessary: they provide feedback, enjoyable, and beneficial. In my opinion walkthroughs could be better if they were used to provide constructive feedback to the teachers on how to become better educators. In my experience, this has not been the case. Most times, walkthroughs are not accompanied by the feedback mechanism that is necessary to help teachers improve their crafts. Evaluators are only looking for what is missing (the negatives) rather than looking for what is present (the positives) during the observation.

The issue of professional development raised many interesting views and discussions as well. The views of my colleagues were that most professional development sessions are conducted just to fulfill schools or district-wide mandates (requirements). There is a huge amount of repetitions on the topics, lack of choice is the norm, and they infringe on teachers’ planning time. This is because most professional development sessions happens during the teachers’ planning periods and after regular school hours. My colleagues and I would welcome diverse professional learning opportunities where teachers would have a choice on what sessions to attend based on personally identified professional development needs.

In addition to our discussions in class, I conducted an interview with my principal to learn more about the process of recruiting a new principal and also the training that administrators receive to conduct LKES and TKES walkthroughs (the interview transcripts are attached on the back of this reflection). I learned from the interview that the training that administrators receive takes only three days. It is more like an orientation rather than a training. During this so called training, administrators are familiarized with the check-list, what to look for during walkthroughs, and how to report the results of a walkthrough on a computer.  I believe this is not enough time for a major task such as this. A task that can determine a teachers’ likelihood of receiving next years’ contract or not, requires more rigorous training than what is happening at the moment. I would like for the training to train administrators to look for more than what happening in the class at that particular time and the 10 minutes that the administrator spends in a class. I believe, administrators should spend more time in class, visit more often, and share ideas on how to improve instruction.

The process of recruiting a principal in the Dekalb County Schools System is very different from one school to the next. In most schools, a principal is normally assigned to a school without local inputs. At Dunwoody High School, the process involves a four-prong process. It involves the members of the community, some members of the school staff, students, and the county hiring process. I like the process at Dunwoody High School as it involves the majority of the schools’ stakeholders. It is more democratic. Dunwoody High School, unlike other schools in the county where a principal is assigned to school, the community, the students’ body, and school staffs are all involved in selecting the incoming principal.

To conclude, in my capacity as an instructional leader, I will work hard to influence those around me on better ways to provide professional development for teachers and administrators. I feel like the current model of one size fits all is not working. I will advocate for diverse professional development training for teachers. Professional development trainings that cater to teachers’ identified needs for development. I believe that with the amount of knowledge I have acquired in the past two years in this program, I am able to influence the micro level decisions on professional development training at my school. I see myself growing further as an educational leader on these issues. I believe through authentic advocacy based on teachers’ identified needs for development, we will be able to improve professional development experiences for teachers. As they say, we can’t keep doing the same things over and over expecting different results.

Reference

Anderson, G. L. (2009). Advocacy leadership: Towards a post-reform agenda in education. New York, NY: Routledge.

Ravitch, D. (2009). Time to ‘kill No Child Left Behind’. Educational Week, 28(33), 30-36.

Spring, J. (2001). The politics of American education. New York, NY: Taylor & Francis.

American Schools: Resource Allocation Is the Problem.


In the past two weeks, we have been discussing eight K-12 major educational issues related to instructional leadership at the macro level. The issues are: Alternative Assessment, Control of the US Department of Education on the Local Department of Education, What Does It Mean for Schools to be Placed on “Alert” Status?, Georgia and Value Added Measurement, Year Round Schools in Georgia and US in General: What Does the Research Says?, How Credible are the SLOs? Issues of Validity and Reliability, SLOs and Multiple Teacher: Who is Held Accountable?, and the CCRPI. In this reflection, due to a multitude of topic covered, I will only touch on one issue that stood out to me personally, the Alternative Testing issue. I will discuss on how I see this issue impacting me in my capacity as an instructional leader. In addition, I will offer my observations on how I may grow as an instructional leader while tackling this issue.

In the past decade, American schools have seen an increase in student assessment especially those in the form of multiple choice. This was brought about due mainly to the introduction of accountability measures after the introduction of the No Child Left Behind legislation in 2002 (Popham, 2010). However, currently there is a push to reduce the impact of high stakes tests on students and school resources (Ravitch, 2009).  Popham argues that, one, multiple choice tests can only assess basic understanding and recall of information and therefore have no value in improving learning especially critical thinking and problem solving skills and two, schools spend a tremendous amount of money to conduct these tests, with money that could be used to otherwise improve learning in schools (Popham, 2010; Ravitch, 2009).

In response to the calls for alternative assessment in schools, many states have come up with some alternative to multiple choice tests. For example, the state of Georgia is introducing the milestone test this year. This test is considered to be much better than the previous ones as it offers students the opportunity to express their understanding of learned information through writing. However, in our discussion we found out that the majority of the test questions are in filling in the bubble format with a few open ended questions at the end. In addition, we also found out that at the elementary level, these tests will be offered on the computer while the majority of elementary students have no training in keyboarding skills and are still struggling with spelling. In my views this is an impending disaster. How can you test students in a platform that they have little to no knowledge of? This is something very dear to me as I have a daughter in an elementary school. My wife and I have been discussing this issue a lot lately. We are planning to hire someone to teach our daughter keyboarding skills so that she can be successful in these tests. However, I ask myself: Is this really necessary? What about those who may not be able to hire someone to teach their kids keyboarding skills? Should their kids fail? These are some of the questions I have been asking myself lately. Unfortunately, there are no easy answers.

As an instructional leader, I feel like this kind of planning at the macro level with little or no input from the school level and especially inputs from teachers is troublesome. If teachers were asked to offer their opinion on the impact of administering a computerized test that requires actual written responses to elementary grade students lacking formal training in keyboarding, I am sure this could be avoided. Maybe the time has come to start listening to teachers before policies of this magnitude gets implemented. Perhaps, we need to stop blaming the teachers for all the woes in education as they knows a thing or two about teaching and learning. Let us use their expertise in teaching and learning to create programs and policies that will improve student learning. After all, teacher spend more time with our kids on a daily basis. Teachers knows our kids possibly more than we do especially when it comes to learning.

I am glad that the milestones will at least include some open ended questions. However, the number of multiple choice questions in these teste are still too high in my views. As an instructional leader, I would like to see a major shift in assessment, from merely testing for recall type of knowledge such as multiple choice questions are capable of, to more alternative types of assessment such as portfolios, performance based assessment, writing components and rubrics (Popham, 2010). I believe that if the ultimate goal of education is to develop students who can think deeper, problem solve, and think critically regarding their roles in society, then, we need assessments that reflect this type of knowing(Ravitch, 2009).

To help make a shift from excessive multiple choice testing format tests, I believe it is my responsibility as an Instructional Leader to share with colleague the research on the current climate of testing and how it is negatively impacting students learning and school resource allocation. The truth is that, America still leads the world on per child expenditure in education. The fact that most of this money is spent on testing is wrong. In my humble opinion, more money should be spend in things that matter most for student learning: teacher salaries, new books, balanced education, technology infusion, and so forth.

In my capacity as an instructional leader, I will work tirelessly to influence those around me on better ways to assess student learning including alternative means such those we discussed in class. I believe that with the amount of knowledge I have acquired in the past two years, I should be able to influence the micro level decisions on testing at my school. In addition, as a parent I have the obligation to discuss these issues with my fellow parents and hopefully together we will be able to voice our opinion on this issue to school administrators at our schools, the district, and the state levels. With a sustained engagement of this kind, I am sure we will see a shift in this testing regime to more nuanced types of assessments. I see myself growing further as an educational leader on this issue, through advocacy.

References

Popham, J. (2010). Everything school leaders needs to know about assessment. Thousand Oaks, CA: SAGE Company.

Ravitch, D. (2009). Time to ‘kill No Child Left Behind’. Educational Week, 28(33), 30-36.