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Gautham Arun; Vivek Perumal; Francis Paul John Bato Urias; Yan En Ler; Bryan Wen Tao Tan; Ranganath Vallabhajosyula; Emmanuel Tan; Olivia Ng; Kian Bee Ng; Sreenivasulu Reddy Mogali – Anatomical Sciences Education, 2024
Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and…
Descriptors: Artificial Intelligence, Teaching Methods, Computational Linguistics, Anatomy
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Jun-Ming Su – Education and Information Technologies, 2024
With the rapid growth of web applications, web application security (WAS) has become an important cybersecurity issue. For effective WAS protection, it is necessary to cultivate and train personnel, especially beginners, to develop correct concepts and practical hands-on abilities through cybersecurity education. At present, many methods offer…
Descriptors: Computer Science Education, Information Security, Computer Security, Web Sites
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Turk, Judith K. – Natural Sciences Education, 2023
Literature circles are student-led, small-group discussions that promote active learning and engagement with literary texts. The objective of this study was to assess the impact of literature circles on student engagement and learning outcomes in a pedology course. For various reading assignments throughout the semester, students either…
Descriptors: Soil Science, Reading Assignments, Science Instruction, Student Attitudes
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McDermott, Maggie; Gullekson, Nicole; Kiersch, Christa; Tempski, Diana – Marketing Education Review, 2021
As marketing educators, we face a challenge to provide innovative and challenging learning environments that respond to student needs. The Integrated Core Program is an innovative approach to enhancing and improving upon undergraduate Principle of Marketing students' mastery of content along with further developing their critical thinking skills.…
Descriptors: Marketing, Mastery Learning, Interdisciplinary Approach, Undergraduate Students
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Shemy, Nader Said – Journal of Education and e-Learning Research, 2022
This research investigates the effect of different levels of constructivist scaffolding within e-content on undergraduate students' mastery of learning and their attitudes towards it. The research sample involves three experimental groups, each group having thirty (30) students. The first group (Group 1) studied e-content with simple…
Descriptors: Mastery Learning, Undergraduate Students, Scaffolding (Teaching Technique), Constructivism (Learning)
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Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
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Mshayisa, Vusi Vincent – Journal of Food Science Education, 2020
In higher education, there are calls to incorporate active learning experiences that place the student at the center of learning, rather than encouraging students to be passive listeners. For students to have a deeper and more meaningful learning experience, educators can use an active learning approach. This approach attempts to engage students…
Descriptors: Student Attitudes, Puzzles, Undergraduate Students, Learning Experience
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Aydogdu, Seyhmus – Education and Information Technologies, 2020
Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
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Condorelli, Andrea; Malchiodi, Dario – Informatics in Education, 2022
We describe a collaboration between Marelli and Università degli Studi di Milano that allowed the latter to add a course on «Architectures for Big Data» in its Master programme of Computer Science, with the aim of providing a teaching approach characterized by an intertwined exposition of discipline, methodology and practical tools. We were…
Descriptors: School Business Relationship, Feedback (Response), Work Environment, Learning Activities
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Bragg, Jedediah E.; Kratz, Jon; Nay, Eden D. E.; Miller-Cribbs, Julie; Munoz, Ricky T.; Howell, Daniel – Journal of Teaching in Social Work, 2020
The integration of evidence-informed practices in social work education can be difficult given the crowded curricula of most Master of Social Work programs, particularly for advanced standing MSW students who launch directly into advanced concentration year coursework after obtaining their Bachelor of Social Work (BSW). Several factors impact…
Descriptors: Social Work, Counselor Training, Evidence Based Practice, Masters Programs
Al-Jarf, Reima – Online Submission, 2023
This article aims to give a comprehensive guide to planning and designing vocabulary tests which include Identifying the skills to be covered by the test; outlining the course content covered; preparing a table of specifications that shows the skill, content topics and number of questions allocated to each; and preparing the test instructions. The…
Descriptors: Vocabulary Development, Learning Processes, Test Construction, Course Content
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LeCloux, Mary – Journal of Teaching in Social Work, 2021
Although social workers are increasingly likely to encounter suicidal clients in their practice, many are under-prepared to address the issue of suicide, and significant deficiencies in suicide education exist in social work graduate programs. This study examined the acceptability and effectiveness of a brief yet comprehensive online module…
Descriptors: Social Work, Counselor Training, Suicide, Graduate Students
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Golenhofen, Nikola; Heindl, Felix; Grab-Kroll, Claudia; Messerer, David A. C.; Böckers, Tobias M.; Böckers, Anja – Anatomical Sciences Education, 2020
Hand-held devices have revolutionized communication and education in the last decade. Consequently, mobile learning (m-learning) has become popular among medical students. Nevertheless, there are relatively few studies assessing students' learning outcomes using m-learning devices. This observational study presents an anatomy m-learning tool…
Descriptors: Anatomy, Undergraduate Students, Telecommunications, Handheld Devices
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Cornelisz, Ilja; Klaveren, Chris – Journal of Computer Assisted Learning, 2018
A prerequisite for low-stakes activities to improve learning is to keep students engaged when confronted with challenging material. Comparing a personalized and non-personalized version of computerized practising, this study experimentally evaluates the relationships between student effort and ability across different dimensions of task…
Descriptors: Learner Engagement, Computer Assisted Instruction, Correlation, Summative Evaluation
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Larson, Benjamin E.; Bohler, Jeffrey A.; Krishnamoorthy, Anand – Journal of Information Technology Education: Innovations in Practice, 2021
Aim/Purpose: Business analytics is a cross-functional field that is important to implement for a college and has emerged as a critically important core component of the business curriculum. It is a difficult task due to scheduling concerns and limits to faculty and student resources. This paper describes the process of creating a central video…
Descriptors: Teaching Methods, Data Analysis, Business Administration Education, Undergraduate Students
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