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Download full textBadrinath, Anirudhan; Wang, Frederic; Pardos, Zachary – International Educational Data Mining Society, 2021
Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…
Descriptors: Models, Markov Processes, Mathematics, Intelligent Tutoring Systems
Vassoyan, Jean; Vie, Jill-Jênn – International Educational Data Mining Society, 2023
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…
Descriptors: Reinforcement, Networks, Simulation, Educational Technology
Miao, Dezhuang; Dong, Yu; Lu, Xuesong – International Educational Data Mining Society, 2020
In colleges, programming is increasingly becoming a general education course of almost all STEM majors as well as some art majors, resulting in an emerging demand for scalable programming education. To support scalable education, teaching activities such as grading and feedback have to be automated. Recently, online judge systems have been…
Descriptors: Programming, Prediction, Error Patterns, Models
Efremov, Aleksandr; Ghosh, Ahana; Singla, Adish – International Educational Data Mining Society, 2020
Intelligent tutoring systems for programming education can support students by providing personalized feedback when a student is stuck in a coding task. We study the problem of designing a hint policy to provide a next-step hint to students from their current partial solution, e.g., which line of code should be edited next. The state of the art…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Computer Science Education, Artificial Intelligence
Emerson, Andrew; Rodríguez, Fernando J.; Mott, Bradford; Smith, Andy; Min, Wookhee; Boyer, Kristy Elizabeth; Smith, Cody; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2019
Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…
Descriptors: Programming, Computer Science Education, Feedback (Response), Prediction
Villamor, Maureen M.; Rodrigo, Mercedes T. – International Educational Data Mining Society, 2017
This paper characterized the extent of collaboration of pairs of novice programmers as they traced and debugged fragments of code using cross-recurrence quantification analysis (CRQA). This was a preliminary analysis that specifically aimed to compare and assess the collaboration of pairs consisting of two individuals who may have different or…
Descriptors: Programming, Eye Movements, Prior Learning, Computer Assisted Instruction
An, Truong-Sinh; Krauss, Christopher; Merceron, Agathe – International Educational Data Mining Society, 2017
The emergence of Massive Open Online Courses (MOOCs) has enabled new research to analyze typical behaviors of learners. In this paper, we investigate whether this research is generalizable to other courses that are backed by a learning management system (LMS) as MOOCs are. Building on methods developed by others, we characterize individual…
Descriptors: Large Group Instruction, Online Courses, Student Behavior, College Students
Majid al-Rifaie, Mohammad; Yee-King, Matthew; d'Inverno, Mark – International Educational Data Mining Society, 2016
This paper proposes a new technique for analysing the behaviour of students on an online course. This work considers a range of social learning behaviours supported in our recently designed and implemented collaborative learning system which supports students giving and receiving feedback on each other's developing work and practice. The course…
Descriptors: Student Behavior, Online Courses, Social Behavior, Data Analysis
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
