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Toshiya Arakawa; Haruki Miyakawa – Technology, Knowledge and Learning, 2025
Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…
Descriptors: Data Science, Educational Games, Statistics Education, Foreign Countries
Khulbe, Manisha; Tammets, Kairit – Technology, Knowledge and Learning, 2023
Insights derived from classroom data can help teachers improve their practice and students' learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of…
Descriptors: Faculty Development, Learning Analytics, Intervention, Teacher Attitudes
Amine Boulahmel; Fahima Djelil; Gregory Smits – Technology, Knowledge and Learning, 2025
Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…
Descriptors: Independent Study, Educational Research, Classification, Educational Indicators
Alturki, Sarah; Hulpu?, Ioana; Stuckenschmidt, Heiner – Technology, Knowledge and Learning, 2022
The tremendous growth of educational institutions' electronic data provides the opportunity to extract information that can be used to predict students' overall success, predict students' dropout rate, evaluate the performance of teachers and instructors, improve the learning material according to students' needs, and much more. This paper aims to…
Descriptors: Grade Prediction, Academic Achievement, Data Use, Dropout Rate
Pillutla, Venkata Sai; Tawfik, Andrew A.; Giabbanelli, Philippe J. – Technology, Knowledge and Learning, 2020
In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or…
Descriptors: Learning Processes, Online Courses, Data Collection, Data Analysis
Tolwinska, Bozena – Technology, Knowledge and Learning, 2021
The aim of the analysis is to present the role of school principals in supporting teachers' skillful use of information and communication technologies in education. The article presents the results of analysis of a fragment of data from a study carried out in 2017 as part of the research project devoted to the specificity of functioning of schools…
Descriptors: Principals, Administrator Role, Technological Literacy, Educational Technology
Delcker, Jan – Technology, Knowledge and Learning, 2023
The influence of digitalisation on society and the workplace require stakeholders in school development to incorporate digital competencies into school curricula. This study examines the occurrence of digital components in 831 curricula of the vocational schools in Baden-Württemberg, Germany with a text mining approach and the analysis of keywords…
Descriptors: Technology Uses in Education, Digital Literacy, Vocational Schools, Curriculum Evaluation
Cardona Zapata, Mónica Eliana; López Ríos, Sonia – Technology, Knowledge and Learning, 2022
Experimental activity in the physics teaching can be considered as a space in which teachers create contexts for students to approach the way scientific knowledge is constructed. In this sense, the strategies for the integration of Information and Communication Technologies (ICT) in the context of science education, has a wide potential to guide…
Descriptors: Physics, Science Instruction, Teaching Methods, Visual Aids
Howell, Joel A.; Roberts, Lynne D.; Seaman, Kristen; Gibson, David C. – Technology, Knowledge and Learning, 2018
Higher education institutions are developing the capacity for learning analytics. However, the technical development of learning analytics has far exceeded the consideration of ethical issues around learning analytics. We examined higher education academics' knowledge, attitudes, and concerns about the use of learning analytics though four focus…
Descriptors: Universities, College Faculty, Teacher Attitudes, Knowledge Level
Winne, Philip H.; Nesbit, John C.; Popowich, Fred – Technology, Knowledge and Learning, 2017
A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules…
Descriptors: Data Collection, Research Methodology, Learning Processes, Computer Software
Van Horne, Sam; Curran, Maura; Smith, Anna; VanBuren, John; Zahrieh, David; Larsen, Russell; Miller, Ross – Technology, Knowledge and Learning, 2018
Instructional technologists and faculty in post-secondary institutions have increasingly adopted learning analytics interventions such as dashboards that provide real-time feedback to students to support student' ability to regulate their learning. But analyses of the effectiveness of such interventions can be confounded by measures of students'…
Descriptors: Chemistry, Science Instruction, Learning Strategies, Questionnaires
Guarcello, Maureen A.; Levine, Richard A.; Beemer, Joshua; Frazee, James P.; Laumakis, Mark A.; Schellenberg, Stephen A. – Technology, Knowledge and Learning, 2017
Supplemental Instruction (SI) is a voluntary, non-remedial, peer-facilitated, course-specific intervention that has been widely demonstrated to increase student success, yet concerns persist regarding the biasing effects of disproportionate participation by already higher-performing students. With a focus on maintaining access for all students, a…
Descriptors: Peer Teaching, Supplementary Education, College Students, Student Participation
Abu Saa, Amjed; Al-Emran, Mostafa; Shaalan, Khaled – Technology, Knowledge and Learning, 2019
Predicting the students' performance has become a challenging task due to the increasing amount of data in educational systems. In keeping with this, identifying the factors affecting the students' performance in higher education, especially by using predictive data mining techniques, is still in short supply. This field of research is usually…
Descriptors: Performance Factors, Data Analysis, Higher Education, Academic Achievement
Liu, Min; Lee, Jaejin; Kang, Jina; Liu, Sa – Technology, Knowledge and Learning, 2016
Using a multi-case approach, we examined students' behavior patterns in interacting with a serious game environment using the emerging technologies of learning analytics and data visualization in order to understand how the patterns may vary according to students' learning characteristics. The results confirmed some preliminary findings from our…
Descriptors: Case Studies, Student Behavior, Behavior Patterns, Games
Seufert, Sabine; Meier, Christoph; Soellner, Matthias; Rietsche, Roman – Technology, Knowledge and Learning, 2019
The increasing prevalence of learner-centred forms of learning as well as an increase in the number of learners actively participating on a wide range of digital platforms and devices give rise to an ever-increasing stream of learning data. Learning analytics (LA) can enable learners, teachers, and their institutions to better understand and…
Descriptors: Incidence, Student Centered Learning, Data Analysis, Prediction