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Effects of Image-based and Text-based Activities onStudent Learning Outcomes
Anne K. GreenbergCRLT
University of Michigan1071 Palmer Commons
100 Washtenaw Ave.Ann Arbor, MI 48109
Melissa GrossMovement Science
University of Michigan3738 Central CampusRecreation Building
401 Washtenaw Ave.Ann Arbor, MI 48109
Mary C. WrightCRLT
University of Michigan1071 Palmer Commons
100 Washtenaw Ave.Ann Arbor, MI 48109
ABSTRACT
Research on benefits of visual learning has relied primarilyon lecture-based pedagogy, not accounting for the process-ing time students need to make sense of both visual andverbal material[8]. In this study, we investigate the poten-tial differential effects of text-based and image-based studentlearning activities on student learning outcomes in a func-tional anatomy course. When controlling for demographicsand prior GPA, participation in in-class image-based activ-ities is significantly correlated with performance on associ-ated exam questions, while text-based engagement is not.Additionally, students rated activities as helpful for seeingimages of key ideas and as being significantly less mentallytaxing than text-based activities.
Categories and Subject Descriptors
H.1.2 [User/Machine Systems]: Human Factors—Hu-
man information processing ; J.3 [Life and Medical Sci-ences]: Health; K.3.1 [Computer Uses in Education]:Collaborative Learning
General Terms
Design, Measurement, Theory
Keywords
LectureTools, active learning, visualizer-verbalizer, dual cod-ing, assessment
1. INTRODUCTIONMany instructors seek the most effective way to present
course material to students, often pairing visual formats(e.g., slide images) with verbal explanations. Indeed, at one
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time, it was thought that a mix of verbal and visual formatswould allow students to encode information in long-termmemory twice[7, 2], thus increasing learning. Surprisingly,there is little evidence for this approach[3, 6]. For exam-ple, Tangen et al.[8] compare student quiz scores followingthree different types of lectures – with visuals relevant tothe content, with visuals not relevant, and with text-basedbullet points – and find no significant difference in accuracyamong them. Lin and Atkinson[5] find similar results, albeitfor animated vs. static graphics.
However, research on visuals may be helpfully contextual-ized by two key factors. First, visual learning formats maybe more beneficial in course contexts requiring the interpre-tation of complex visual material [3, 4], such as anatomyor art history. Second, research on learning through visual-verbal presentations has relied primarily on lecture-basedpedagogy, not accounting for the processing time studentsneed to make sense of both pieces of information[5, 8]. There-fore, we offer a important case study of student learning inan anatomy course at the University of Michigan. Anatomyis a discipline with a significant visual component, for stu-dents to recognize and identify corporeal elements such asbones, ligaments, and muscles. Additionally, this course de-votes significant in-class time to active learning, which wehypothesize allows for the cognitive processing needed to en-hance student learning. Previous studies have treated activelearning as a separate condition from visual and text-basedlearning (e.g., Tangen et al.[8], and Bockhoven[1]), but weseek to investigate their integration.
2. METHODSThe study analyzes data from a University of Michigan
class, Human Musculoskeletal Anatomy, a sophomore-levelcourse required for all students majoring in Movement Sci-ence. Taught fall and winter terms, the course averages101 students, and it is comprised of about 60% MovementScience majors and 40% non-majors. The class providesstudents with an in-depth knowledge of the musculoskeletalsystem in order to better understand the functional relation-ships between human musculoskeletal anatomy and bodymovement.
Each class session consists of lecture segments punctuatedwith active learning activities in which students work inde-pendently or in pair-share dyads to answer interactive ques-
Figure 1: Examples of in-class activities
tions asked through LectureTools, interactive presentationsoftware (Fig. 1). Both text-based and image-based activi-ties are included in each class session. Text-based activitiesconsist of a written question and multiple-choice answers.Image-based activities consist of either a question associ-ated with a particular image (and multiple-choice answers)or an image map where students are asked to click on theimage in order to answer the question.Student participation on all learning activities is tracked
using LectureTools analytics data. The number of activitiesin which a student participated is collected for each student.Student learning outcomes are assessed via exam questionscores. Individual exam questions are written to correspondto single lecture topics (and therefore either image-based ortext-based learning activities). Care is taken to write examquestions of equivalent difficulty. Regression analyses areused to look for correlations between student scores on ex-ams and student participation in learning activities. Demo-graphic data including gender, underrepresented minoritystatus, and cumulative GPA are also included in analyses.Additionally, students were asked to participate in a end-
of-semester survey, which asked them to reflect on how much”mental activity” (i.e., cognitive load) was required whenparticipating in image- and text-based activities. Surveyquestions were modeled on the instrument for measuringcognitive load described by Lin & Atkinson[5]. Student re-sponse rate was 88%.
3. INITIAL FINDINGS AND DISCUSSIONWe predicted that participation in all learning activities
would be positively correlated with student-learning out-comes. However, given the visual nature of the disciplineand active learning format, we hypothesized that partic-ipation in image-based learning activities would be morestrongly correlated with exam scores than participation intext-based activities.Students reported that with active learning, image-based
activities present less of a cognitive load. Nearly all students(95%) agreed or strongly agreed that LectureTools learningactivities were helpful for ”seeing images of key ideas in thecourse.” Additionally, on a scale of 1 to 8, with one cor-responding to ”easy” and 8 corresponding to ”demanding”mental activity, students rated image-based activities as 4.14(SD=1.83) and text-based activities as 4.78 (SD=1.81), astatistically significant difference (p<0.0001).Linear regressions suggest that participation in both text-
based (r=0.46) and image-based (r=0.47) in-class activitiesare correlated with performance on associated exam ques-tions (p<.0001). However, when GPA is taken into accountusing multivariate regression, participation on text-basedquestions is no longer significantly correlated with examgrade (Table 1), indicating that higher performing students
Table 1: Regression model predicting exam perfor-mance with in-class participation and demographicvariables. R
2=0.418. URM status and gender arecoded as dichotomous variables, with male=0 andfemale=1, and non-URM=0 and URM=1.
Estim. SE p-valueIntercept 34.6547 9.0839 0.0003Image Participation 0.7844 0.2927 0.009Text participation 0.2391 0.4090 0.56URM status 4.6957 7.0671 0.51Gender -13.7643 4.0102 0.0009GPA 4.6383 2.0907 0.03
(based on GPA) are more likely to participate in text-basedquestions. This is not the case for image-based questions, in-dicating that participation in image-based in-class questionsraises exam scores.
The active learning classroom is an ideal setting for ad-vancing our understanding of how text-based and image-based materials support student learning. In the activelearning setting, students have more time to process infor-mation, thus reducing cognitive load and potentially increas-ing deeper learning, particularly with image-based activities.
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