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Direct linkKaren M. Lionello-DeNolf; David Eckerman; Rebecca Hise; Elizabeth Pinzino; Roger Ray – Journal of Applied Behavior Analysis, 2025
Procedural fidelity is an important component of behavioral intervention programs. The "Train-to-Code" software was used to teach skilled observation of implementation of three types of discrete-trial programs, and improvement to procedural fidelity was assessed. Participants completed a training package that involved coding video…
Descriptors: Fidelity, Computer Assisted Instruction, Applied Behavior Analysis, Behavior Modification
Download full textPriti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2024
Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…
Descriptors: Student Evaluation, Computer Assisted Testing, Artificial Intelligence, Comprehension
Haley A. Delcher; Enas S. Alsatari; Adeyeye I. Haastrup; Sayema Naaz; Lydia A. Hayes-Guastella; Autumn M. McDaniel; Olivia G. Clark; Devin M. Katerski; Francois O. Prinsloo; Olivia R. Roberts; Meredith A. Shaddix; Bridgette N. Sullivan; Isabella M. Swan; Emily M. Hartsell; Jeffrey D. DeMeis; Sunita S. Paudel; Glen M. Borchert – Biochemistry and Molecular Biology Education, 2025
Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how…
Descriptors: Artificial Intelligence, Technology Uses in Education, Training, Teaching Methods
Jiangang Hao; Wenju Cui; Patrick Kyllonen; Emily Kerzabi; Lei Liu; Michael Flor – Journal of Educational Measurement, 2025
Collaborative problem solving is widely recognized as a critical 21st-century skill. Assessing collaborative problem solving depends on coding the communication data using a construct-relevant framework, and this process has long been a major bottleneck to scaling up such assessments. Based on five datasets and two coding frameworks, we…
Descriptors: Cooperative Learning, Problem Solving, 21st Century Skills, Automation
Larsen, Tori M.; Endo, Bianca H.; Yee, Alexander T.; Do, Tony; Lo, Stanley M. – CBE - Life Sciences Education, 2022
Bloom's taxonomy is a classification of learning objectives originally developed for general educational purposes. The taxonomy was revised to expand beyond cognitive processes and to include knowledge types as an orthogonal dimension. As Bloom's taxonomy is a tool widely used in biology education by researchers and instructors, it is important to…
Descriptors: Taxonomy, Educational Objectives, Cognitive Processes, Verbs
Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
Chun-Ying Chen – ACM Transactions on Computing Education, 2025
This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…
Descriptors: Models, Learning Motivation, Cognitive Processes, Difficulty Level
Mayer, Christian W. F.; Ludwig, Sabrina; Brandt, Steffen – Journal of Research on Technology in Education, 2023
This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…
Descriptors: Prompting, Classification, Artificial Intelligence, Natural Language Processing
Eman Abdullah AlOmar – ACM Transactions on Computing Education, 2025
Large Language Models (LLMs), such as ChatGPT, have become widely popular for various software engineering tasks, including programming, testing, code review, and program comprehension. However, their impact on improving software quality in educational settings remains uncertain. This article explores our experience teaching the use of Programming…
Descriptors: Coding, Natural Language Processing, Artificial Intelligence, Computer Software
Wang, Cixiao; Xu, Lingling; Liu, Hui – Journal of Computer Assisted Learning, 2022
Background: Virtual manipulatives (VMs) are increasingly adopted in inquiry activities. However, the effects of the ratio of mobile device-based VMs to students and external scripts (a guiding structure for prompting group process) provision on group interaction has not been detailed. Objectives: This study proposed four different technology…
Descriptors: Manipulative Materials, Educational Technology, Handheld Devices, Cooperative Learning
McCrink, Koleen; Perez, Jasmin; Baruch, Erica – Developmental Psychology, 2017
Toddlers performed a spatial mapping task in which they were required to learn the location of a hidden object in a vertical array and then transpose this location information 90° to a horizontal array. During the vertical training, they were given (a) no labels, (b) alphabetical labels, or (c) numerical labels for each potential spatial location.…
Descriptors: Prompting, Spatial Ability, Cognitive Mapping, Toddlers
Video Prompting to Teach Robotics and Coding to Middle School Students with Autism Spectrum Disorder
Wright, John C.; Knight, Victoria F.; Barton, Erin E.; Edwards-Bowyer, Meghan – Journal of Special Education Technology, 2021
Video-based modeling is an evidence-based practice for teaching social and communication skills, functional and daily living skills, and some academic skills (i.e., math) to students with autism spectrum disorder. The efficacy of video-based modeling, however, has not yet been established for STEM skills related to science, technology, or…
Descriptors: Video Technology, Prompting, Coding, Programming
Keeler, Jessie M.; Koretsky, Milo D. – Journal of Chemical Education, 2016
Based on a previous analysis of student reflection responses, we developed and implemented a hybrid reflection activity that allowed students to choose among a "Muddiest Point" prompt or a "Most Surprised" prompt, or to use both. We examined and coded student responses from two different courses and determined that each prompt…
Descriptors: Student Attitudes, Prompting, Chemistry, Science Instruction
Wright, John C. – ProQuest LLC, 2019
Video-based modeling is an evidence-based practice for teaching social and communication skills, functional and daily living skills, and some academic skills to students with autism spectrum disorder. The efficacy of video-based modeling, however, has not yet been established for STEM skills related to science, technology, or engineering. Drawing…
Descriptors: Video Technology, Prompting, Robotics, Coding
Harney, Owen M.; Hogan, Michael J.; Quinn, Sarah – International Journal of Computer-Supported Collaborative Learning, 2017
In a society which is calling for more productive modes of collaboration to address increasingly complex scientific and social issues, greater involvement of students in dialogue, and increased emphasis on collaborative discourse and argumentation, become essential modes of engagement and learning. This paper investigates the effects of…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Prompting, Persuasive Discourse
