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Kerstin Huber; Maria Bannert – Journal of Computing in Higher Education, 2024
The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining…
Descriptors: Learning Processes, Data Analysis, Navigation (Information Systems), Student Behavior
Shan Li; Xiaoshan Huang; Tingting Wang; Juan Zheng; Susanne P. Lajoie – Journal of Computing in Higher Education, 2025
Coding think-aloud transcripts is time-consuming and labor-intensive. In this study, we examined the feasibility of predicting students' reasoning activities based on their think-aloud transcripts by leveraging the affordances of text mining and machine learning techniques. We collected the think-aloud data of 34 medical students as they diagnosed…
Descriptors: Information Retrieval, Artificial Intelligence, Prediction, Abstract Reasoning
Daniel F. O. Onah; Elaine L. L. Pang; Jane E. Sinclair – Journal of Computing in Higher Education, 2024
Despite the proliferation of massive open online courses (MOOCs) and the impressive levels of enrolment they attract, many participants do not complete these courses. High drop-out has been identified as one of the major problems with existing MOOC formats. Our work addresses two factors relating to non-completion. Firstly, MOOCs require a high…
Descriptors: MOOCs, Self Management, Independent Study, Educational Technology
Linjing Wu; Shuang Yu; Qingtang Liu; Junmin Ye; Xinxin Zheng; Jianhu Wang – Journal of Computing in Higher Education, 2025
Interdisciplinary collaboration is widely used in research, industry, and education. Understanding the differences in cognitive processes between cross-discipline and same-discipline groups can improve instruction in collaborative learning. In this study, students volunteered to participate in cross-discipline or same-discipline collaborative…
Descriptors: Intellectual Disciplines, Cooperative Learning, Comparative Analysis, Interdisciplinary Approach
Li, Xu; Ouyang, Fan; Chen, WenZhi – Journal of Computing in Higher Education, 2022
Group formation is a critical factor which influences collaborative processes and performances in computer-supported collaborative learning (CSCL). Automatic grouping has been widely used to generate groups with heterogeneous attributes and to maximize the diversity of students' characteristics within a group. But there are two dominant challenges…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Group Dynamics, Grouping (Instructional Purposes)
Lahav, Orly; Talis, Vadim; Cinamon, Rachel Gali; Rizzo, Albert – Journal of Computing in Higher Education, 2020
The virtual interactive consulting agent system is an online virtual career center that supports freshman students in transition to higher education. This virtual counseling system, based on accumulative empirical knowledge for working students and knowledge about effective career intervention, aims to guide first-year university students in…
Descriptors: Computer Mediated Communication, Computer Assisted Instruction, College Bound Students, College Freshmen
Schwarzenberg, Pablo; Navon, Jaime; Pérez-Sanagustín, Mar – Journal of Computing in Higher Education, 2020
The flipped classroom gives students the flexibility to organize their learning, while teachers can monitor their progress analyzing their online activity. In massive courses where there are a variety of activities, automated analysis techniques are required in order to process the large volume of information that is generated, to help teachers…
Descriptors: Models, Blended Learning, Teaching Methods, Electronic Learning
Lin, Shu-Yuan; Xie, Ying – Journal of Computing in Higher Education, 2019
Student-generated tagclouds provided an intuitive overview of a group of learners' collective knowledge. Although such tagclouds may have the potential to be used as effective learning tools, it has not been clear how students use this tool for knowledge construction. In this paper, we report a two-stage study that investigated college students'…
Descriptors: Computer Software, College Students, Concept Mapping, Intervention
Shadiev, Rustam; Sun, Ai – Journal of Computing in Higher Education, 2020
In this study, we applied a combination of speech-to-text recognition (STR) and computer-aided translation (CAT) technologies during lectures in English as a foreign language to facilitate student comprehension of the lecture content. The instructor lectured in English, the STR system generated texts from the voice input, and the CAT system then…
Descriptors: Assistive Technology, Speech Communication, Computer Assisted Instruction, Translation
Shin, Donghee; Park, Seyoung – Journal of Computing in Higher Education, 2019
As an instructional material, 3D instructions afford people to learn procedural-manipulative tasks. Observing and emulating motions presented in 3D animations is important in learning contexts. This study examined the effects of visual cueing in an effort to identify the optimal way to present information in a 3D virtual environment. While…
Descriptors: Teaching Methods, Creativity, Computer Software, Animation
Mohsen, Mohammed Ali; Mahdi, Hassan Saleh – Journal of Computing in Higher Education, 2021
Video captioning has been investigated extensively in the Computer-Assisted Language Learning (CALL) literature to aid second language vocabulary acquisition. However, a little is known about how video captioning could foster learners' pronunciation, which is a component of second language vocabulary acquisition proposed by Nation (Nation,…
Descriptors: Vocabulary Development, Second Language Learning, Second Language Instruction, English (Second Language)
García Botero, Gustavo; Questier, Frederik; Cincinnato, Sebastiano; He, Tao; Zhu, Chang – Journal of Computing in Higher Education, 2018
Research on mobile learning indicates that students perceive mobile devices mainly as communication and entertainment tools. Therefore, a key factor in successful mobile learning implementation is the initial measurement of students' acceptance of those devices into their learning. Countless language applications available suggest that mobile…
Descriptors: College Students, Electronic Learning, Computer Attitudes, Computer Assisted Instruction
Xiong, Yao; So, Hyo-Jeong; Toh, Yancy – Journal of Computing in Higher Education, 2015
The main purpose of this study was to develop an instrument that assesses university students' perceived readiness for computer-supported collaborative learning (CSCL). Assessment in CSCL research had predominantly focused on measuring "after-collaboration" outcomes and "during-collaboration" behaviors while…
Descriptors: Test Construction, College Students, Readiness, Computer Assisted Instruction
Simonson, Michael; Schlosser, Charles; Orellana, Anymir – Journal of Computing in Higher Education, 2011
Distance education is defined, the various approaches for effective research are summarized, and the results of major research reviews of the field are explained in this article. Additionally, two major areas of research are included--research on barriers to the adoption of distance education and research summaries that explain and support best…
Descriptors: Distance Education, Literature Reviews, Definitions, Research Methodology
Shea, Peter; Bidjerano, Temi – Journal of Computing in Higher Education, 2009
In this paper we make the case that online learning continues to grow at a rapid rate and that understanding this innovative mode of education requires analysis that is both conceptually and empirically driven. This study inquires into the concept of "cognitive presence" a multivariate measure of significant learning derived from the Community of…
Descriptors: Multivariate Analysis, Learner Engagement, Construct Validity, Correlation