Class Absence, Instructor Lecture Notes, Intellectual Styles, and Learning Outcomes
Oskar Harmon, William Alpert, Archita Banik & James Lambrinos
Atlantic Economic Journal ISSN 0197-4254 Atl Econ J DOI 10.1007/s11293-015-9470-6
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Author's personal copy Atl Econ J DOI 10.1007/s11293-015-9470-6
Class Absence, Instructor Lecture Notes, Intellectual Styles, and Learning Outcomes Oskar Harmon 1 & William Alpert 1 & Archita Banik 2 & James Lambrinos 3
# International Atlantic Economic Society 2015
Abstract At many universities, undergraduate introductory economics courses are taught in large lecture halls. Casual empiricism suggests that rates of student absenteeism are significantly greater in the large lecture format compared to the smaller classroom format. There is also the compounding factor that numerous empirical studies have identified a statistically significant negative relationship between absenteeism and student performance. Using panel data, it is estimated that the average student with less than perfect attendance is better off attending the lecture, but studying from instructorprovided lecture notes can significantly reduce the negative effect of absence on exam performance. Additional estimates of the differential effects of intellectual styles show the notes were the least beneficial for the auditory intellectual style. Keywords Learning preferences . Learning styles . Intellectual styles . Absenteeism . Lecture notes . Online . Economic education . Blended . Hybrid . PowerPoint JEL A20
Introduction Concern for attendance and the allure of new technologies are pushing innovations into the classroom where Principles of Economics is taught. At large universities, the economics is plain, as the instructional delivery of choice for teaching Principles of Economics is the large lecture hall. Anecdotal evidence confirms what common sense
* Oskar Harmon
[email protected] 1
University of Connecticut, Storrs, CT, USA
2
Bloomsburg University of Pennsylvania, Bloomsburg, PA, USA
3
Union Graduate College, Schenectady, NY, USA
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tells us, that rates of student absenteeism are higher for this class format than for the small lecture format. Surveys of instructional methods (Becker and Watts 1996; Coates and Humphreys 2003) report a growing number of instructors use technology to augment the traditional chalk and talk method of delivery of Principles of Economics. Though the cost of adopting new technology is high (e.g., a steep learning curve for new software, ongoing costs related to maintenance and updating files, and keeping up with technological advances and upgrades to software), many instructors are adopting technology because of the promise of net positive impacts on learning outcomes (Goffe and Sosin 2005; Sosin et al. 2008). For example, among the benefits of online delivery are elimination of distance commuting, accommodation of schedule conflicts, and a variety of learning materials accommodating different learning preferences. On the other hand, among the costs of online delivery are reduced student-to-student and instructor-to-student interactions, and a possible mismatch between the independent learning skills and maturity required of online users and those possessed by the typical undergraduate student. The findings of several empirical studies of adopting new technologies suggest a gradual approach (Gratton-Lavoie and Stanley 2009, has an excellent summary). A specific gradual approach to technological innovation adopted by some instructors is that of making available to students the lecture notes of the PowerPoint presentation used for the “live” lecture. These notes can assist a student with note taking and can be a substitute if a student does not attend a lecture. Note taking is a complex task that involves simultaneously utilizing the skills of listening, organizing, and writing (Grabe 2005). Because some students are more accomplished at the task than are others, the instructor-provided lecture notes can reduce the time spent on creating an organized outline, and free time up to spend on listening and understanding. For students with poor note-taking skills, this can make a significant difference in whether they are able to create lecture notes suitable for reviewing for an exam (Chen and Lin 2008b; Grabe 2005). Another benefit is the instructor’s lecture notes are a potential supplement for students unable to attend class because of an unavoidable or unpredictable scheduling conflict. On the other hand, however, instructor-provided lecture notes could have the negative impact of lowering rates of class attendance. Ultimately, whether instructorprovided lecture notes adversely effect learning outcomes depends on a complex set of factors including student learning preferences, student skills, unpredictable scheduling conflicts, and the student’s goal for their course grade.
Review of the Literature The numerous empirical studies of the effect of attendance on learning outcomes in principles of economics classes uniformly report a negative and statistically significant relationship. The early studies of Principles of Economics classes (Romer 1993) used exam scores and attendance records. More recent studies (Chen and Lin 2008a; Marburger 2001, 2006) use panel data of individual exam questions and attendance at the lectures where the subject material of these questions was covered. These studies estimate a model where the dependent variable is an indicator variable for whether or not the question is answered correctly, and the independent variables consist of an indicator variable for absent, and there are also variables to control for student
Author's personal copy Class Absence, Instructor Lecture Notes, Intellectual Styles, and...
characteristics. These studies uniformly report a statistically significant negative effect of absenteeism on student exam performance. Absence from class occurs for all manner of reasons, and often it is not the result of an undervaluation of education. It can be because of illness, unavoidable scheduling conflicts with other academic, athletic, or job-related commitments, or a mismatch between the lecture format and the student’s intellectual learning style. This study seeks to broaden the scope of the usual explanatory variables to include learning supplements available to offset the learning missed due to absence, and include cognitive attributes that affect learning from the traditional lecture format. Specifically this study seeks to contribute to the existing literature by examining the effects of lecture notes and intellectual styles on the relationship between class attendance and learning outcomes. Note taking during lectures is an important variable influencing learning outcomes (Chen and Lin 2008b). There is a large literature in the field of education and psychology that measures the effects of note taking and note reviewing on student performance (Grabe 2005). For students with good note-taking skills, note taking in class has positive benefits associated with making a personalized record of the lecture. However, for students with poor note-taking skills, note taking in class has the disadvantage of leaving the student with an inadequate record of the lecture, distracting the student from the full benefit of listening to a lecture, and curtailing the benefits of reviewing the lecture notes (Grabe 2005). For a course in psychology, Grabe (2005) investigated the correlation between student use of instructor-provided online lecture notes, absenteeism, and the effect on student performance. In the introductory psychology class of 183 students, 48 students (26 %) did not make use of the lecture notes. It is reported that the mean exam score for users of lecture notes was significantly higher than for non-users of lecture notes. Of the students viewing the lecture notes, 75 % had viewed them six or more times. When asked how frequently they printed out the lecture notes and used them during lecture, 20 % reported they did not use the lecture notes in this way, and 80 % responded they had used them in this way, of which 42 % had done so six or more times. Also examined was use of lecture notes as a replacement for class attendance. The students who viewed the lecture notes six or more times were asked how frequently they used lecture notes as a replacement for attending class. Twenty-one percent responded they had never used the lecture notes to replace attending class, and 28 % responded they had used the notes for this purpose. Furthermore, it was reported that the mean exam score of the two groups was not significantly different. There are at least two interesting implications of these findings. When instructor lecture notes are provided, 75 % of the students opted to view them and of that group 75 % viewed them frequently. When the lecture notes were used frequently, they were an effective way for students to make up the material when absent from class. The empirical study of (Chen and Lin 2008b) confirms the positive effect of lecture notes on learning outcomes for a Principles of Economics class. Their sample consisted of 126 students from an intermediate microeconomics course at an elite public university in Taiwan. The instructor lectured from a PowerPoint presentation and the slides were made available on a university server three to five days prior to each lecture. Their study examined whether the exam scores of the students who downloaded the PowerPoint lecture notes prior to attending the live lecture differed from the exam scores of students who did not download the slides prior to attending the live lecture. In their findings, they report that the effect of downloading the lecture notes prior to
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lecture is positive, statistically significant, and slightly larger than the effect of attending the lecture without having previously downloaded the lecture notes. An implication is that downloading the lecture notes prior to attending the lecture improved the learning outcomes relative to students who attended the lecture without the benefit of the lecture notes. Another important factor potentially influencing learning outcomes is intellectual learning style (Zhang et al. 2012: Renzulli and Smith 1984) and the possible mismatch with the lecture format or available learning supplements. These are effects which, to our knowledge, have not yet been studied in the economic education literature on attendance and learning outcomes. If a student’s intellectual style is not well suited to the available lecture supplements (e.g., lecture notes), then the educational returns for that student may be lower than for other students. Alternatively, if a student’s intellectual style is not well suited for live lecture, then the return to the supplements may be higher than for other students. There is an extensive literature in the field of educational psychology examining intellectual styles as an approach for understanding how students absorb and process information, and the effect on learning outcomes. If intellectual styles are consistently correlated with instructional methods and learning outcomes, then identifying and matching intellectual styles with instructional methods will increase the efficiency of the learning process (Zhang et al. 2012). An example of this line of research is (Hamadea and Artailb 2010), which examines the correlation of intellectual styles with learning outcomes for a training course in Computer Assisted Design (CAD). Using the (Barsch 1996) intellectual style inventory, their study identifies the intellectual styles of 44 students in the course. The authors track the time to construct, test, and improve four CAD models developed during the training period. They identify an intellectual style correlated with efficiency in construction of CAD models, and another intellectual style correlated with degree of sophistication of the CAD models. From this evidence, they suggest that efficiencies in the CAD production process can be realized by the assignment of engineers with activist intellectual styles to the parts and assemblies stage of producing CAD models, and placing engineers with reflective, intuitive, or global intellectual styles in the downstream stages of altering and testing CAD models. A similar example in the field of accounting is Wynn-Williams et al. 2008. Several empirical studies illustrate the potential of intellectual styles research for improving learning outcomes in the instruction of Principles of Economics courses. The (Boatman et al. 2008) study used the visual audio read/write kinesthetic (VARK) index of intellectual styles (Fleming 2012) and reported a positive correlation between student performance and a strong preference for the visual intellectual style. Noting the reliance on diagrammatic explanations in widely used introductory economics textbooks, they comment that students with a preference for visual presentation will likely do well in economics courses. Conversely, supplementing diagrams with non-visual based explanations of economic concepts may increase learning outcomes for students with intellectual styles that are not predominated by a visual preference. Another example of the potential of intellectual styles research is implied in the findings reported by (Brown and Liedholm 2002). This study compares learning outcomes of students in an introductory economics course where one set received instruction in the traditional lecture format and the other received instruction in an online format. Their findings are that the learning outcomes for students in the online delivery format were
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handicapped relative to those for students in the traditional delivery format. The authors speculate that the outcome may be explained by the students in the online section not having the strong independent learning skills needed to do well in an online environment. An implied potential benefit of the (Brown and Liedholm 2002) findings is that, by identifying student intellectual styles, academic advisors could better advise students on course selection where mode of instructional delivery is a variable in the mix (Boatman et al. 2008). Other studies show that learning preferences consistently differ between online students and traditional students in enrolled classes (Diaz and Cartnal 1999; Halsne and Gatta 2002), and a consistent link between learning preferences and learning outcomes (Charkins et al. 1985; Hall 1982). Most recently, (Bethune 2010), taking a slightly different approach than the prior studies in the economics of education literature of class attendance, compares the magnitude of the attendance effect relative to other factors affecting student performance. He reports that while absenteeism has a statistically significant negative effect, prior academic success as measured by grade point average (GPA) and college admission test scores, mainly the Scholastic Aptitude Test (SAT), has a larger positive and statistically significant effect. He argues that his results suggest attendance is overemphasized in prior studies, and suggests future research give more attention to uncovering other factors, in addition to attendance, that influence learning outcomes. Our study, in the spirit of Bethune, addresses two issues not previously examined. Can usage of instructor-provided lecture notes offset the adverse impact of absence from live lecture? Do student intellectual styles influence the benefit from usage of instructor-provided lecture notes?
Data The data for this study are collected from an undergraduate introductory economics course with an enrollment of 125 students at a large northeastern public university. The course is taught from the approach of an informed citizen’s guide to the economy and to economic ideas. Students passing the course may still take Principles of Microeconomics or Macroeconomics for course credit. It is primarily taken by nonmajors and taught in a traditional large lecture format. Class meets twice weekly. Lecture notes in the form of PowerPoint slides, which are used in the live lecture, are made available for students to download. The data come from three sources. Clickers were used to record attendance. Attendance was taken in 16 of 24 (66 %) lectures. Information on intellectual styles, usage of the instructor-provided lecture notes, and demographic characteristics was collected from a student survey. Seventy-two students (58 %) returned completed questionnaires. The source for student academic characteristics was the college transcript. The collection of data and solicitation of student consent was done in accordance with the university protocols for use of human subjects in research. A profile of a student’s intellectual style is compiled from student responses to 16 questions. The questions are from the University of South Dakota inventory of learning styles (University of South Dakota 2012) and a copy of the questions is available for free use (Reece 2007). For each question, the first response (A) indicates a “visual” learner, the second response (B) an “auditory” learner, and the third response (C) a
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“kinesthetic” learner. The South Dakota Inventory describes the learning styles as: “Visual is a preference for learning by seeing and looking; Auditory is a preference for learning by hearing and listening; and, Kinesthetic is a preference for learning by touching and doing” (University of South Dakota 2012). For this study, students are classified as having a predominate learning style of auditory, kinesthetic, or visual if 40 % of the responses are a particular learning style and the responses for each of the other two styles are each less than 33 %. Response patterns that are not classified as a predominate style are classified as multi-modal. For example, out of 16 questions, if a student response pattern is eight (50 %) auditory responses, four (25 %) kinesthetic responses, and four (25 %) visual, then the classification is an auditory learner. Using this algorithm, the distribution of students in the sample across the four intellectual style categories is most heavily concentrated in the multi-modal category: 54 % (39) are multi-modal, 22 % (16) are auditory, 14 % (10) are kinesthetic, and 10 (7 %) are visual. Table 1 compares the descriptive statistics for the sample divided by student selfreported response to a question of whether they were ever absent from class, to which 20 responded never absent, and 52 responded absent sometimes. The never absent group differs from the absent group in only a few ways. The never absent have a higher GPA (at a 6 % significance level). This is consistent with the expectation that lower attendance rates are associated with lower academic achievement. None of the sophomores are in the never absent group. Sophomores comprise only 15 % (11) of the total, whereas freshman comprise 61 % (44), and 24 % (17) are upperclassmen. The relatively lower self-reported absence rate of sophomores stands as an anomaly compared to the freshmen and the upperclassmen. All of visual learners are in the Table 1 Student characteristics by whether ever absent Never Absent
Sometimes Absent
N
Mean
S.D.
Final Exam Score
19
68.00
GPA
18
3.14
credits enrolled
19
15.26
Economics or Engineering Major
20
0.45
Freshman
20
0.70
0.47
Sophomore
20
0.00
0.00
Junior
20
0.10
0.31
Pr(|T| > |t|)
N
Mean
S.D.
9.31
48
67.79
11.22
0.42
49
2.81
0.70
1.94
52
14.54
2.53
0.26
0.51
52
0.56
0.50
0.41
52
0.58
0.50
0.34
52
0.21
0.41
0.02 *
52
0.08
0.27
0.75
0.94 0.06 +
Senior
20
0.20
0.41
52
0.12
0.32
0.35
have job
20
0.65
0.49
51
0.69
0.47
0.77
visual intellectual style
20
0.00
0.00
52
0.19
0.40
0.03 *
auditory intellectual style
20
0.30
0.47
52
0.19
0.40
0.33
kinesthetic intellectual style
20
0.10
0.31
52
0.10
0.30
0.96
multi-modal intellectual style
20
0.60
0.50
52
0.52
0.50
0.54
Observations
20
Absolute t statistics in parentheses +
p
