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Shortt, Mitchell; Tilak, Shantanu; Kuznetcova, Irina; Martens, Bethany; Akinkuolie, Babatunde – Computer Assisted Language Learning, 2023
More than 300 million people use the gamified mobile-assisted language learning (MALL) application (app) Duolingo. The challenging tasks, reward incentives, systematic levels, and the ranking of users according to their achievements are just some of the elements that demonstrate strong gamification elements within this popular language learning…
Descriptors: Gamification, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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
Uluyol, Çelebi; Orak, Esma; Gökçearslan, Sahin; Ramazanoglu, Mehmet – Participatory Educational Research, 2023
This study is designed to reveal the research trends of graduate theses published in the field of computer programming in K-12 between 2018 and 2022. Document analysis was used for data collection in this study. The data was divided into 9 categories, and the results demonstrated that the scholars in the Departments of Computer Educational and…
Descriptors: Computer Science Education, Programming, Kindergarten, Elementary Secondary Education
Ostrow, Korinn S.; Wang, Yan; Heffernan, Neil T. – Journal of Learning Analytics, 2017
Data is flexible in that it is molded by not only the features and variables available to a researcher for analysis and interpretation, but also by how those features and variables are recorded and processed prior to evaluation. "Big Data" from online learning platforms and intelligent tutoring systems is no different. The work presented…
Descriptors: Data, Comparative Analysis, Scoring, Mathematics Skills
Ostrow, Korinn S.; Wang, Yan; Heffernan, Neil T. – Grantee Submission, 2017
Data is flexible in that it is molded by not only the features and variables available to a researcher for analysis and interpretation, but also by how those features and variables are recorded and processed prior to evaluation. "Big Data" from online learning platforms and intelligent tutoring systems is no different. The work presented…
Descriptors: Data, Comparative Analysis, Scoring, Mathematics Skills
Nwosu, Jonathan Chinaka; John, Henry Chukwudi; Akorede, O. J. – Educational Research and Reviews, 2018
This study assessed the availability and use of ICT-based Instructional tools in selected medical colleges in Ogun State, Nigeria. This study adopted a descriptive survey research design. The population to be studied is medical lecturers (328), clinical instructors (42) and laboratory technologist (92) from Ben Carson Snr. Medical School, Babcock…
Descriptors: Information Technology, Medical Education, Medical Students, Sampling
Saeed, Farah Jamal Abed Alrazeq; Al-Zayed, Norma Nawaf – International Journal of Education and Literacy Studies, 2018
The study aimed at investigating the attitudes of Jordanian undergraduate students towards using computer assisted-language learning (CALL) and its effectiveness in the process of learning the English language. In order to fulfill the study's objective, the researchers used a questionnaire to collect data, followed-up with semi-structured…
Descriptors: Undergraduate Students, Student Attitudes, Computer Assisted Instruction, Teaching Methods
Yeh, Hui-Chin – Computer Assisted Language Learning, 2015
Few studies have investigated how metacognitive processes foster the application of genre knowledge to students' academic writing. This is largely due to its internal and unobservable characteristics. To bridge this gap, an online writing system based on metacognition, involving the stages of planning, monitoring, evaluating, and revising, was…
Descriptors: Metacognition, Statistical Analysis, Academic Discourse, Sampling
Jairam, Dharmananda; Kiewra, Kenneth A.; Kauffman, Douglas F.; Zhao, Ruomeng – Contemporary Educational Psychology, 2012
This study investigated how best to study a matrix. Fifty-three participants studied a matrix topically (1 column at a time), categorically (1 row at a time), or in a unified way (all at once). Results revealed that categorical and unified study produced higher: (a) performance on relationship and fact tests, (b) study material satisfaction, and…
Descriptors: Computer Assisted Instruction, Investigations, Item Sampling, Learning
Buteau, Chantal; Jarvis, Daniel H.; Lavicza, Zsolt – Canadian Journal of Science, Mathematics and Technology Education, 2014
In this article, we outline the findings of a Canadian survey study (N = 302) that focused on the extent of computer algebra systems (CAS)-based technology use in postsecondary mathematics instruction. Results suggest that a considerable number of Canadian mathematicians use CAS in research and teaching. CAS use in research was found to be the…
Descriptors: Computer Assisted Instruction, Mathematics Instruction, National Surveys, Foreign Countries
Annamalai, Nagaletchimee; Tan, Kok Eng – The EUROCALL Review, 2015
Little research in the ESL context has examined the online teaching and learning activities in high schools. One main reason is the lack of appropriate theoretical framework rather than the learners or the environment. Using data from twelve high school students and two teachers from two Malaysian schools, the current study adapted Borup et al.'s…
Descriptors: English (Second Language), Second Language Learning, Check Lists, Writing Instruction
Arnold, Pip; Pfannkuch, Maxine; Wild, Chris J.; Regan, Matt; Budgett, Stephanie – Journal of Statistics Education, 2011
Computer simulations and animations for developing statistical concepts are often not understood by beginners. Hands-on physical simulations that morph into computer simulations are teaching approaches that can build students' concepts. In this paper we review the literature on visual and verbal cognitive processing and on the efficacy of…
Descriptors: Foreign Countries, Statistics, Learning Theories, Cues
Jarvela, Sanna; Veermans, Marjaana; Leinonen, Piritta – Social Psychology of Education: An International Journal, 2008
The aim of this article is to describe and analyze how computer supported inquiry learning effects two secondary school students' engagement in a literacy learning project. With comparative analysis of various sources of data we aim to understand what engagement is, how and why it changes over time and how changes in engagement are reflected in…
Descriptors: Content Analysis, Comparative Analysis, Literacy, Secondary School Students
Raiche, Gilles; Blais, Jean-Guy – Applied Psychological Measurement, 2006
Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their…
Descriptors: Computer Assisted Instruction, Computer Software, Sampling, Adaptive Testing
Cook, Tony; Rushton, Brian S. – Science Software Quarterly, 1984
Reviews a computer-assisted learning package (available from CONDUIT) which introduces survey and sampling techniques by pretending that the user is a pollster asking one of six questions of a more or less political nature. Documentation and performance are rated fair while ease of use is considered excellent. (JN)
Descriptors: Computer Assisted Instruction, Computer Software, Higher Education, Research Methodology
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