Student Learning in an Accelerated Introductory Biology Course Is Significantly Enhanced by a Flipped-Learning Environment.

CBE Life Sci Educ

Department of Mathematics and Natural Sciences, College of Letters and Sciences, National University, San Diego, CA 92037.

Published: September 2018

AI Article Synopsis

  • A flipped-classroom model shifts content delivery to home through short videos while maximizing in-class activities for enhanced learning.
  • Students in a flipped-classroom accelerated biology course scored significantly higher on quizzes compared to those in a traditional setting at two different assessment points.
  • The positive outcomes were particularly noted in students' recall of basic concepts and biology vocabulary, suggesting that this approach benefits foundational learning.

Article Abstract

A flipped-classroom environment generally strives to create more in-class time for activities that enhance student learning, while shifting some content delivery to outside the classroom through the use of short didactic videos. We compared a flipped-classroom setting with the traditional ("control") setting for an accelerated lower-division general biology course. Student self-reporting and video analytics functions showed ample and variable video viewing among individual students. Student learning was evaluated through quizzes administered after a set of concepts were covered (post 1) and at the end of the course (post 2). Students in the flipped sections had significantly higher quiz scores than students in the control sections for both post 1 and post 2. Analyses of variance analyzing the effect of and interactions between type of instruction, in-class activities, time, and Bloom's level of the quiz questions found significant differences in the overall model and all the factors, except for the presence and level of activities. Significant differences between students in the flipped and control sections were observed for low-level Bloom's questions only. Thus, the positive effect of the flipped-classroom approach on student learning may be due to improvements in recall of basic concepts and a better understanding of biology vocabulary in their first biology course.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234803PMC
http://dx.doi.org/10.1187/cbe.17-07-0129DOI Listing

Publication Analysis

Top Keywords

student learning
16
biology course
12
students flipped
8
control sections
8
student
5
learning accelerated
4
accelerated introductory
4
biology
4
introductory biology
4
course
4

Similar Publications

Application of ChatGPT-assisted problem-based learning teaching method in clinical medical education.

BMC Med Educ

January 2025

Department of Urology, Xiangya Hospital, Central South University, Changsha, Hunan, 410000, China.

Introduction: Artificial intelligence technology has a wide range of application prospects in the field of medical education. The aim of the study was to measure the effectiveness of ChatGPT-assisted problem-based learning (PBL) teaching for urology medical interns in comparison with traditional teaching.

Methods: A cohort of urology interns was randomly assigned to two groups; one underwent ChatGPT-assisted PBL teaching, while the other received traditional teaching over a period of two weeks.

View Article and Find Full Text PDF

Background: Effective pharmacotherapy requires strong collaboration between physicians and pharmacists, highlighting the need for interprofessional education (IPE) in university curricula. This study evaluated the impact of an IPE program on medical and pharmacy students, focusing on their perceived development of interprofessional collaborative competencies, perceived learning outcomes, and clinical collaboration perceptions.

Methods: A mixed-method approach was employed to evaluate an IPE program that consisted of three mandatory activities with increased complexity and autonomy, that were integrated into the medical and pharmacy students' curricula.

View Article and Find Full Text PDF

In order to reduce the number of parameters in the Chinese herbal medicine recognition model while maintaining accuracy, this paper takes 20 classes of Chinese herbs as the research object and proposes a recognition network based on knowledge distillation and cross-attention - ShuffleCANet (ShuffleNet and Cross-Attention). Firstly, transfer learning was used for experiments on 20 classic networks, and DenseNet and RegNet were selected as dual teacher models. Then, considering the parameter count and recognition accuracy, ShuffleNet was determined as the student model, and a new cross-attention mechanism was proposed.

View Article and Find Full Text PDF

Dental Students' Learning Experience: Artificial Intelligence vs Human Feedback on Assignments.

Int Dent J

January 2025

Department of Basic Sciences, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, 20400 Sri Lanka. Electronic address:

Objective: This study evaluated the effectiveness of an AI-based tool (ChatGPT-4) (AIT) vs a human tutor (HT) in providing feedback on dental students' assignments.

Methods: A total of 194 answers to two histology questions were assessed by both tutors using the same rubric. Students compared feedback from both tutors and evaluated its accuracy against a standard rubric.

View Article and Find Full Text PDF

The integration of artificial intelligence (AI) into dental imaging has led to significant advancements, particularly in the analysis of panoramic radiographs, also known as orthopantomograms (OPGs). One emerging application of AI is in determining gender from these radiographs, a task traditionally performed by forensic experts using manual methods. This systematic review and meta-analysis aim to evaluate the accuracy of AI algorithms in gender determination using OPGs, focusing on the reliability and potential clinical and forensic applications of these technologies.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!