The Effect of the Inverted Classroom Teaching Approach on Student/Faculty Interaction and Students’ Self-Efficacy
Bibliographic record
Abstract
Abstract The Effect of the Inverted Classroom Teaching Approach on Student/Faculty Interaction and Students’ Self-Efficacy Research PaperThe inverted or flipped classroom approach provides students with the opportunity to develop abasic understanding of core concepts through the online delivery of short pre-lecture videos.This in turn, enables the course instructor to make us of the in-class time more effectively bycreating an active learning environment. This approach has been used to teach an electric andmagnetic fields physics course as part of the second-year electrical and computer engineeringcurriculum at a large research-intensive engineering school. The teaching approach consisted of(a) pre-class lesson videos with embedded viewing quizzes (average length of 25 minutes), and(b) in-class active learning opportunities, including conceptual questions and peer instructionfacilitated through a classroom-response system, group work exercises, and opportunities forindividual work and review of the material at hand.As part of the two-year study associated with this new initiative, one of the key researchquestions was: Does the new teaching approach improve the students’ perception ofstudent/instructor interaction and the students’ self-efficacy as compared to the traditionalinstructor-centered approach? To assess this, a mixed-methods design was used whichincluded, in part, an end-of-course survey and follow-up focus group sessions. The studyinvolved teaching the course in a traditional lecture format in one year, and then with theinverted classroom technique the next year. The same instructor taught the course in both years,and approximately 330 students took the course each year. The same survey and focus groupprotocols were used for the inverted classroom cohort (number of survey respondents = 186) ashad been used the previous year for the traditional lecturing cohort (number of surveyrespondents = 178).It was found that overall, students from the inverted classroom cohort had higher satisfactionratings for the level of their interaction with the instructor during class (mean=3.92 versus 3.58, p< .001, on a scale of 5, with “strongly dissatisfied” being 1 and “strong satisfied” being 5). Aswell, 70% of students in the inverted course versus 51% of the students in the traditional courseexpressed satisfaction with this type of interaction. Students in the inverted class also reportedthat they interacted with the instructor during class more often than the traditionally-taughtstudents (mean = 2.61 versus 1.86, p < .001, on a 6-point scale with “never” being 1 and “morethan once a week” being 6). Particularly, 25% of the inverted-class students versus 54% of thetraditionally-taught students reported that they had never interacted with the instructor duringclass. These survey findings have been confirmed by the comments from the student focusgroup sessions.The students’ self-efficacy survey questions were based on the well-known LAESE(Longitudinal Assessment of Engineering Self-Efficacy) instrument. Factor analysis has shownthat the 31 items on the self-efficacy survey were significantly loaded on three factors: (a)Ability to learn the course material, (b) Ability to explain the fundamental course concepts toothers, and (c) the Ability to succeed in engineering. For all three factors, students in bothcohorts expressed high levels of self-efficacy, and there were no significant differences betweenthe mean values observed for both cohorts. Students in the inverted cohort had the mostconfidence in their ability to learn the material in the course (mean = 5.24, on a scale of 7) andhad the least confidence in their ability to explain the course concepts to one of their peers (mean= 4.42, on a scale of 7).As this new teaching approach becomes more widespread, it is important to ensure that thistechnique improves all aspects of the student learning experience. The results from this initialstudy indicate that improvements can be made to the students’ perception and satisfaction withstudent/faculty interaction, while no significant impact was found with course-specific andengineering self-efficacy of the students. Future offerings of this course with this approach willincorporate more specific efforts to leverage the opportunity of the inverted classroom to developstudents’ self-motivation for learning and engagement with the material. In this way we wouldhope to see an improvement in the students’ course-related self-efficacy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".