Background: Educators are experiencing undue pressure to perform in education accountability driven by evidence-based instruction. The pressure to show adequate student performance on standardized tests causes many educators to allocate a larger portion of their classroom instructional time to test preparation instead of teaching higher-order learning and thinking skills (Tapia & Marsh, 2004). The shift in teaching time allocation also causes educators to sacrifice other crucial teaching and learning components believed to improve student learning. Other educational components include: student interest, motivation, self–confidence, the value of the subject matter, and enjoyment (Chamberlin, 2010). In this article, I will define the term student affect, present the evolution of this psychological construct, present some of the challenges of measuring it, explain why I plan to measure student affect in my dissertation research study, and finally I will conclude by explaining affect as it relates to my dissertation research.
Definition of the “Term Student Affect.”
The term affect in the field of psychology carries many meanings. It is referred to as motivation (Chouinard and Roy, 2008 & Shin, Lee, & Kim, 2009 as cited in Chamberlin, 2010), dispositions (Gresalfi, 2009 as cited in Chamberlin, 2010), belief (as cited in Chamberlin, 2010), emotions (Grootenboer, 2003 as cited in Chamberlin, 2010), and attitudes (Chouinard & Roy, 2008 as cited in Chamberlin, 2010). The myriad of terms is sometimes confusing. However, Anderson and Bourke (2000) define affect as a construct consisting of sub-components such as “anxiety, aspiration(s), value, attitude (s), interest(s), and locus of control, self-efficacy, and self-esteem” (p.1). Furthermore, Anderson and Bourke (2010) argue that motivation and affect are two words that carries the same meaning because motivation is shown throughout all sub-components of affect. Thus, the term affect is a complex psychological construct expressed in various words with similar and/or sometimes carrying same meaning.
The Evolution of the Construct and its Measurement
The psychological construct, affect, gained recognition in the early 20th century, however, researchers did not have instruments or inventories to measure or quantify it at that time (Thompson, 1992 as cited in Chamberlin, 2010). In the 1920’s and 1930’s affect was considered a non-observable behavior due to an immense interest in behaviorist research. A type of research that concentrated in investigating observable behavior. Because of that, little interest and effort was directed to non- behaviorist research. Thus, researchers of that time period paid little or no attention to the research on student affect.
However, in the 1960’s and 1970’s affect re-gained traction again due to a new breed of researchers. In the past 40 years there has been increased attention to the research regarding affect, especially by researchers in mathematics, science, and the social sciences. During that time, researchers attempted to define, characterize, and develop instruments for measuring student affect in mathematics more than in any other subject areas. The sheer number of instruments developed to assess affect during this period is colossal and therefore, it is not to list them all here, however, I will mention a few of the most popular instruments. A summary of the popular instruments used to measure affects’ sub- components is presented in Table 1 below:
Summary of Student Affect Instruments
Name of Instrument Acronym Affect Sub-Component Grade Level Person(s) Who Conducted the Study
Attitude Towards Mathematics Inventory AtMI Self-efficacy, Value, Anxiety, and Motivation Secondary: High School Tapia & Marsh
Mathematics Attitude Scale None Value and enjoyment Tertiary: Freshman in College Aiken
Mathematics Anxiety Rating Scale MARS Anxiety Tertiary: Freshman to Senior. Richardson & Suinn
Fennema-Sherman Mathematics Attitude Scale None Attitude, Self-Efficacy, Anxiety, and Motivation. Secondary: High School Fennema & Sherman
National Longitudinal Study of Mathematical Ability NLSMA Attitude Secondary: Grade 8 School Math Study Group
Challenges Associated with Measuring Students’ Affect
The biggest barrier to measuring affect is the fact that affect is a psychological construct. Adding to the complexity and difficulty in measuring affect is the fact that affect is composed of many sub-components, namely, anxiety, aspiration, attitude, interest, locus of control, self-control/efficacy, self-esteem, and value. Since affect is a psychological construct it clearly consists of non-measurable attributes. Unlike measurable attributes such as length, weight, and height in which (we as a society) have agreed upon units of measurements like Meters for length, Kilograms for weight, Kelvin for temperature, affect attributes such as anxiety, self-confidence, and enjoyment do not have society agreed upon measuring units and therefore are far more difficult to measure (Chamberlin, 2010). Moreover, another fact that makes measuring affect difficult is that each of affects’ sub-component consists of three characteristics. These characteristics of affect are: target, direction, and intensity. Target refers to the objective, activity, or idea to which the feeling is directed. Direction refers to the negative or positive direction of the feelings. Finally, intensity refers to the strength degree of the feeling. Thus, with the lack of an agreed upon measurement unit and the many characteristics associated with affect, it is indeed difficult to measure.
Quantifying affects’ sub-components is complex and problematic, but, not impossible. Recently, some psychologists have successfully attempted to quantify and assess some aspects of student affect using sophisticated statistical programs and software in schools. However, a great deal of the research regarding affect still lacks empirical evidence (Tapia & Marsh, 2004). Thus, in light of these promising developments in measuring affect, I plan to assess three sub-components of affect in my dissertation research study. I believe self-confidence, enjoyment, and value of the subject matter are important factors to measure as they related more closely to student performance in an academic setting. I will not include other sub-components of affect (i.e., anxiety, aspiration, attitude, interest, locus of control) in my dissertation research study since they are not closely related with my research topic and course of study.
Why I Plan to Measure Student Affect in my Dissertation Research Study?
Affect is an important ingredient for learning. In 1916, Binet and Simon stated that non- intellectual characteristics were the greatest single most important factor affecting student teaching and hence, their learning (Chamberlin, 2010). The non-intellectual characteristics they referred to at the time is what we call today student affect. The name student affect has changed over the years from non-intellectual characteristics, to non-cognitive characteristics, to it’s modern day name of affect. Unfortunately at the time, Binet and Simon did not conduct experimental studies nor did they have empirical evidence to either support or discredit their claim. However, currently there is ample of evidence from the Trends for International Science Education (TIMMS) supporting the idea that student affect is as important as cognitive components of teaching and learning (Martin & Kelly, 1996, Martin & Foy, 2008; Messick, 1979; as cited in Chamberlin, 2010). The only anomalous data from TIMMS are those by Mullis, Martin, Gonzalez, and Chrostowski (2004). This study did not show a correlation between student affect and academic achievement.
The central focus of my dissertation topic is to determine whether when a students’ learning style preferences are matched with instructional materials, if the student academic achievement will improve. As I continue to examine this hypothesis, I plan to also investigate students affect as one of the factors affecting student learning. I plan to focus upon the investigation of the three components of student affect, namely, self-confidence, perceived value of the subject matter, and whether students will enjoy instruction when the learning materials matches their learning style preference. To do this, I plan to use a modified public domain affect inventory instrument created by Drs. W. James Popham of the University of California, Los Angeles (UCLA) and Rick Stiggins of ETS Assessment Training Institute. Both are experts in educational assessment. Therefore, this instrument will help me collect data to assess the three components of student affect in my research study.
This inventory instrument is similar to the one developed by Aiken (1974) and it assesses student enjoyment, self-efficacy, and how students value the subject matter. This instrument was chosen because it is user-friendly, appropriate for high school students, has high validity and reliability, and produces results that are easy to interpret. Thus, this dissertation research study will include a section on student affect assessment and target the three sub-components of affect, namely, enjoyment, self-efficacy, and value. I believe this will add value to the findings of the present research on student affect and fill-in an prominent gap in these two areas of research in education namely student affect and the Students’ learning style theory.
Aiken, L.R. (1974). Two scale of attitude toward mathematics. Journal for Research in Mathematics Education, 5, 67-71.
Anderson, L. W., & Bourke, S. F. (2000). Assessing affective characteristics in the schools. Mahwah, NJ: Erlbaum.
Chamberlin, S. A. (2010). A review of the instruments created to assess affect in mathematics. Journal of Mathematics Education, 3(1), 167-182.
Mullis, I.V.S., Martin, M.O., Gonzalez, E.J., & Chrostowski, S.J. (2004). TIMSS 2003 International Mathematics: Report Findings from IEA’s Trends in International Mathematics and Science Study at the Fourth and Eighth Grades. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
Tapia, M., & Marsh, G. E. (2004). An instrument to measure affect. Mathematics Education Quarterly, 8(2), 56-62.