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Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
Hu, Xiao; Ng, Jeremy T. D.; Chu, Samuel K. W. – International Journal of Computer-Supported Collaborative Learning, 2022
Learning analytics (LA) and group awareness tools are regarded as top priorities for research in the field of computer-supported collaborative learning. As such, this study investigated whether LA-enabled group awareness information facilitates wiki-supported collaborative learning in secondary education. We proposed an analytic framework of…
Descriptors: Learning Analytics, Collaborative Writing, Cooperative Learning, Secondary Education
Changhao Liang; Rwitajit Majumdar; Yuta Nakamizo; Brendan Flanagan; Hiroaki Ogata – Interactive Learning Environments, 2024
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…
Descriptors: Algorithms, Group Dynamics, Group Activities, Learning Analytics
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Hershkovitz, Arnon; Sitman, Raquel; Israel-Fishelson, Rotem; Eguíluz, Andoni; Garaizar, Pablo; Guenaga, Mariluz – Interactive Learning Environments, 2019
Many worldwide initiatives consider both creativity and computational thinking as crucial skills for future citizens, making them a priority for today's learners. We studied the associations between these two constructs among middle school students (N = 57), considering two types of creativity: a general creative thinking, and a specific…
Descriptors: Creativity, Creative Thinking, Computation, Computer Assisted Instruction
Ericsson, Elin; Sofkova Hashemi, Sylvana; Lundin, Johan – Cogent Education, 2023
Speaking in a foreign language is considered challenging to both teach and learn. Virtual humans (VHs), as conversational agents (CAs), provide opportunities to practise speaking skills. Lower secondary school students (N = 25) engaged in an AI-based spoken dialogue system (SDS) and interacted verbally with VHs in simulated everyday-life scenarios…
Descriptors: Artificial Intelligence, English (Second Language), Second Language Learning, Second Language Instruction
Bronson Hui; Björn Rudzewitz; Detmar Meurers – Language Learning & Technology, 2023
Interactive digital tools increasingly used for language learning can provide detailed system logs (e.g., number of attempts, responses submitted), and thereby a window into the user's learning processes. To date, SLA researchers have made little use of such data to understand the relationships between learning conditions, processes, and outcomes.…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Learning Processes
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Kenneth Holstein; Gena Hong; Mera Tegene; Bruce M. McLaren; Vincent Aleven – Grantee Submission, 2018
When used in classrooms, personalized learning software allows students to work at their own pace, while freeing up the teacher to spend more time working one-on-one with students. Yet such personalized classrooms also pose unique challenges for teachers, who are tasked with monitoring classes working on divergent activities, and prioritizing…
Descriptors: Middle School Teachers, Mathematics Teachers, Technology Uses in Education, Educational Technology
Cook, Michael; Ross, Steven M. – Center for Research and Reform in Education, 2022
The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on mathematics achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) mathematics assessment. This study compared mathematics achievement growth of students who used…
Descriptors: Mathematics Achievement, Mathematics Instruction, Program Evaluation, Individualized Instruction
Cook, Michael; Ross, Steven M. – Center for Research and Reform in Education, 2022
The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on ELA achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) ELA assessment. This study compared the ELA achievement growth in the 2020-21 school year of students who…
Descriptors: English, Language Arts, Computer Assisted Instruction, Computer Assisted Testing
Gobert, Janice D.; Kim, Yoon Jeon; Sao Pedro, Michael; Kennedy, Michael; Betts, Cameron – Grantee Submission, 2015
Many national policy documents underscore the importance of 21st century skills, including critical thinking. In parallel, recent American frameworks for K-12 Science education call for the development of critical thinking skills in science, also referred to as science inquiry skills/practices. Assessment of these skills is necessary, as indicated…
Descriptors: Learning Analytics, Science Education, Teaching Methods, 21st Century Skills
Sánchez, Inmaculada Arnedillo, Ed.; Isaias, Pedro, Ed.; Ravesteijn, Pascal, Ed.; Ongena, Guido, Ed. – International Association for Development of the Information Society, 2019
These proceedings contain the papers and posters of the 15th International Conference on Mobile Learning 2019, which was organised by the International Association for Development of the Information Society and co-organised by the University of Applied Sciences, in Utrecht, The Netherlands, April 11-13, 2019. The Mobile Learning 2019 Conference…
Descriptors: Electronic Learning, Educational Research, Learning Analytics, Internet
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies