Free, publicly-accessible full text available October 13, 2024
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
-
more » « less
Abstract Background Despite well‐documented benefits, instructor adoption of active learning has been limited in engineering education. Studies have identified barriers to instructors’ adoption of active learning, but there is no well‐tested instrument to measure instructors perceptions of these barriers.
Purpose We developed and tested an instrument to measure instructors’ perceptions of barriers to adopting active learning and identify the constructs that coherently categorize those barriers.
Method We used a five‐phase process to develop an instrument to measure instructors’ perceived barriers to adopting active learning. In Phase 1, we built upon the Faculty Instructional Barriers and Identity Survey (FIBIS) to create a draft instrument. In Phases 2 and 3, we conducted exploratory factor analysis (EFA) on an initial 45‐item instrument and a refined 21‐item instrument, respectively. We conducted confirmatory factor analysis (CFA) in Phases 4 and 5 to test the factor structure identified in Phases 2 and 3.
Results Our final instrument consists of 17 items and four factors: (1) student preparation and engagement; (2) instructional support; (3) instructor comfort and confidence; and (4) institutional environment/rewards. Instructor responses indicated that time considerations do not emerge as a standalone factor.
Conclusions Our 17‐item instrument exhibits a sound factor structure and is reliable, enabling the assessment of perceived barriers to adopting active learning in different contexts. The four factors align with an existing model of instructional change in science, technology, engineering, and mathematics (STEM). Although time is a substantial instructor concern that did not comprise a standalone factor, it is closely related to multiple constructs in our final model.
-
In this study, we examined the relation between students’ affective and behavioral response to active learning, the influence of students’ belongingness and their self-efficacy on these responses, and the moderating influence of students’ gender-identity. We found that, despite mean differences in value, positivity, and distraction, there were not gender differences in the pattern of relations between variables. For both groups, belongingness and self-efficacy independently predicted students’ affective response and their evaluation of the class. Belongingness also predicted students’ participation in class. These findings suggest that student-level factors play an important role in how students respond to active learning and that fostering an atmosphere that supports both self-efficacy and belongingness may be beneficial for all students.more » « less
-
Active learning increases student learning, engagement, and interest in STEM and subsequently, the number and diversity of graduates. Yet, its adoption has been slow, partially due to instructors’ concerns about student resistance. Consequently, researchers proposed explanation and facilitation instructional strategies designed to reduce this resistance. Using surveys from 2-year and 4-year institutions including minority-serving institutions, we investigate the relationship between students’ affective and behavioral responses to active learning, instructors’ use of strategies, and active learning type. Analyses revealed low levels of student resistance and significant relationships between both explanation and facilitation strategy use and positive student responses.more » « less
-
null (Ed.)The construct of active learning permeates undergraduate education in science, technology, engineering, and mathematics (STEM), but despite its prevalence, the construct means different things to different people, groups, and STEM domains. To better understand active learning, we constructed this review through an innovative interdisciplinary collaboration involving research teams from psychology and discipline-based education research (DBER). Our collaboration examined active learning from two different perspectives (i.e., psychology and DBER) and surveyed the current landscape of undergraduate STEM instructional practices related to the modes of active learning and traditional lecture. On that basis, we concluded that active learning—which is commonly used to communicate an alternative to lecture and does serve a purpose in higher education classroom practice—is an umbrella term that is not particularly useful in advancing research on learning. To clarify, we synthesized a working definition of active learning that operates within an elaborative framework, which we call the construction-of-understanding ecosystem. A cornerstone of this framework is that undergraduate learners should be active agents during instruction and that the social construction of meaning plays an important role for many learners, above and beyond their individual cognitive construction of knowledge. Our proposed framework offers a coherent and actionable concept of active learning with the aim of advancing future research and practice in undergraduate STEM education.more » « less
Full Text Available