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Qiwei He; Qingzhou Shi; Elizabeth L. Tighe – Grantee Submission, 2023
Increased use of computer-based assessments has facilitated data collection processes that capture both response product data (i.e., correct and incorrect) and response process data (e.g., time-stamped action sequences). Evidence suggests a strong relationship between respondents' correct/incorrect responses and their problem-solving proficiency…
Descriptors: Artificial Intelligence, Problem Solving, Classification, Data Use
Bogdan Simion; Lisa Zhang; Giang Bui; Hancheng Huang; Ramzi Abu-Zeineh; Shrey Vakil – ACM Transactions on Computing Education, 2025
Although ample research has focused on computing skill development over a single course or specific programming language, relatively little attention is paid to how computing skills evolve across a program. Our work aims to understand how specific skills develop throughout a progression of CS courses. We use qualitative content analysis to catalog…
Descriptors: Skill Development, Computer Science Education, Computer Literacy, Prerequisites
Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo – Journal of Computer Assisted Learning, 2023
Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…
Descriptors: Data Use, Group Dynamics, College Students, Cooperative Learning
Hamid Sanei; Jennifer B. Kahn; Rabia Yalcinkaya; Shiyan Jiang; Changzhao Wang – Journal of Science Education and Technology, 2024
Data and computational literacies empower youth to be active participants and future leaders in our increasingly data-driven society. We conducted a design-based research project in which a small group (n = 5) of high school youth from diverse backgrounds learned how to code and create data visualizations and stories with public data about climate…
Descriptors: Coding, Data Use, Science and Society, Story Telling
Sandra Vecchio – Teaching Science, 2025
Being able to learn from failure is a fundamental skill for a scientist, as scientists often learn from failure in practical work by trialling and refining experimental designs, improving calibration techniques, and hypothesising and testing expected outcomes. This qualitative, practice-based study describes how junior secondary science teachers…
Descriptors: Seismology, Failure, Secondary School Science, Science Teachers
Jongsawas Chongwatpol – Education and Information Technologies, 2024
The philosophy for information system (IS)-related projects, such as artificial intelligence (AI) projects, embodies systematic and scientific approaches, that encompass the development, use, and applications of IS by focusing on the interactions among individuals, organizations, and society. However, many organizations still need to learn more…
Descriptors: Artificial Intelligence, Information Systems, Thinking Skills, Design
Liu, Fang; Zhao, Liang; Zhao, Jiayi; Dai, Qin; Fan, Chunlong; Shen, Jun – IEEE Transactions on Learning Technologies, 2022
Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…
Descriptors: Data Use, Learning Management Systems, Problem Solving, Learning Processes
Wang, Karen D.; Cock, Jade Maï; Käser, Tanja; Bumbacher, Engin – British Journal of Educational Technology, 2023
Technology-based, open-ended learning environments (OELEs) can capture detailed information of students' interactions as they work through a task or solve a problem embedded in the environment. This information, in the form of log data, has the potential to provide important insights about the practices adopted by students for scientific inquiry…
Descriptors: Data Use, Educational Environment, Science Process Skills, Inquiry
Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
Dong, Yihuan; Marwan, Samiha; Shabrina, Preya; Price, Thomas; Barnes, Tiffany – International Educational Data Mining Society, 2021
Over the years, researchers have studied novice programming behaviors when doing assignments and projects to identify struggling students. Much of these efforts focused on using student programming and interaction features to predict student success at a course level. While these methods are effective at early detection of struggling students in…
Descriptors: Navigation (Information Systems), Academic Achievement, Learner Engagement, Programming
Michael Moore; David Clingenpeel – College and University, 2024
Wake Forest University (WFU) is in the midst of a 28-month student information system (SIS) transition. The authors' offices are deeply involved in this process on a daily basis. As the university collects and analyzes data, discusses operational needs with campus colleagues, builds and configures tenants, tests and validates, and implements a new…
Descriptors: Registrars (School), Universities, Information Systems, Online Systems
Leslie Dial; Juliann Sergi McBrayer; Antonio P. Gutierrez de Blume; Caitlin Criss; Mary Josephine Carney – Georgia Educational Researcher, 2025
School leadership in education is thinking, communicating, and modeling to maximize student growth and achievement. This quantitative research study explored how school leadership can strengthen the academic progress of students within Multi-Tiered Systems of Support (MTSS). When implementation of MTSS is guided by adaptive school leadership,…
Descriptors: Leadership, Role, Multi Tiered Systems of Support, Communication (Thought Transfer)
Salles, Franck; Dos Santos, Reinaldo; Keskpaik, Saskia – Large-scale Assessments in Education, 2020
During this digital era, France, like many other countries, is undergoing a transition from paper-based assessments to digital assessments in education. There is a rising interest in technology-enhanced items which offer innovative ways to assess traditional competencies, as well as addressing problem solving skills, specifically in mathematics.…
Descriptors: Foreign Countries, Didacticism, Mathematics Tests, Learning Analytics
Jiang, Yang; Gong, Tao; Saldivia, Luis E.; Cayton-Hodges, Gabrielle; Agard, Christopher – Large-scale Assessments in Education, 2021
In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…
Descriptors: Data Use, Learning Analytics, Test Items, Measurement
Eichmann, Beate; Goldhammer, Frank; Greiff, Samuel; Brandhuber, Liene; Naumann, Johannes – Journal of Educational Psychology, 2020
In large-scale assessments, performance differences across different groups are regularly found. These group differences (e.g., gender differences) are often relevant for educational policy decisions and measures. However, the formation of these group differences usually remains unclear. We propose an approach for investigating this formation by…
Descriptors: Problem Solving, Data Use, Differences, Achievement Tests
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