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Gamon Savatsomboon; Prasert Ruannakarn; Phamornpun Yurayat; Ong-art Chanprasitchai; Jibon Kumar Sharma Leihaothabam – European Journal of Psychology and Educational Research, 2024
Using R to conduct univariate meta-analyses is becoming common for publication. However, R can also conduct multivariate meta-analysis (MMA). However, newcomers to both R and MMA may find using R to conduct MMA daunting. Given that, R may not be easy for those unfamiliar with coding. Likewise, MMA is a topic of advanced statistics. Thus, it may be…
Descriptors: Educational Psychology, Multivariate Analysis, Evaluation Methods, Data Processing
Austin M. Shin; Ayaan M. Kazerouni – ACM Transactions on Computing Education, 2024
Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…
Descriptors: Feedback (Response), Programming, Student Projects, Computer Software
Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
Ernesto Panadero; Alazne Fernández Ortube; Rebecca Krebs; Julian Roelle – Assessment & Evaluation in Higher Education, 2025
Rubrics play a crucial role in shaping educational assessment, providing clear criteria for both teaching and learning. The advent of online rubric platforms has the potential to significantly enhance the effectiveness of rubrics in educational contexts, offering innovative features for assessment and feedback through the creation of erubrics.…
Descriptors: Scoring Rubrics, Teaching Methods, Learning Processes, Feedback (Response)
Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Jannik Aagerup; Rui Wang; Ben W. Mol; Wentao Li; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature…
Descriptors: Integrity, Randomized Controlled Trials, Participant Characteristics, Computer Software
Jiangang Hao; Alina A. von Davier; Victoria Yaneva; Susan Lottridge; Matthias von Davier; Deborah J. Harris – Educational Measurement: Issues and Practice, 2024
The remarkable strides in artificial intelligence (AI), exemplified by ChatGPT, have unveiled a wealth of opportunities and challenges in assessment. Applying cutting-edge large language models (LLMs) and generative AI to assessment holds great promise in boosting efficiency, mitigating bias, and facilitating customized evaluations. Conversely,…
Descriptors: Evaluation Methods, Artificial Intelligence, Educational Change, Computer Software
Leen Adel Gammoh – Education and Information Technologies, 2025
This qualitative study examines the risks educators in Jordan face with the integration of ChatGPT, an emerging AI technology, into academic settings. While considerable attention has been given to risks affecting university students, there remains a gap in understanding the specific challenges encountered by educators themselves. Through…
Descriptors: Foreign Countries, Artificial Intelligence, Educational Technology, Technology Integration
Emmanuel Senior Tenakwah; Gideon Boadu; Emmanuel Junior Tenakwah; Michael Parzakonis; Mark Brady; Penny Kansiime; Shannon Said; Sarah Eyaa; Raymond Kwojori Ayilu; Ciprian Radavoi; Alan Berman – Knowledge Management & E-Learning, 2025
The development and introduction of AI language models have transformed the way humans and institutions interact with technology, enabling natural and intuitive communication between humans and machines. This paper conducts a competence-based analysis of ChatGPT's task responses to provide insights into its language proficiency, critical analysis…
Descriptors: Higher Education, Evaluation Methods, Artificial Intelligence, Computer Software
Xue Zhou; Lilian Schofield – Journal of Learning Development in Higher Education, 2024
This paper proposes a conceptual framework for integrating Artificial Intelligence (AI) into the curriculum. It builds on previous conceptual papers, which provided initial suggestions on integrating AI into teaching. The approach to developing the conceptual framework includes drawing on existing frameworks, AI literature, and case studies from…
Descriptors: Artificial Intelligence, Technological Literacy, Technology Integration, Curriculum Development
Farkhanda Qamar; Naveed Ikram – Education and Information Technologies, 2024
Curriculum and its operative application have always been of key importance in educational system and its significance increases when it comes to higher education. The importance of an efficient and effective curriculum is acknowledged in recent studies, but the mechanisms used for preparation of curriculum are still human-intensive, tedious, and…
Descriptors: Undergraduate Study, Evaluation Methods, Engineering Education, Computer Software
Kane Meissel; Esther S. Yao – Practical Assessment, Research & Evaluation, 2024
Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…
Descriptors: Computer Software, Programming Languages, Effect Size, Correlation
Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
Robert C. Lorenz; Mirjam Jenny; Anja Jacobs; Katja Matthias – Research Synthesis Methods, 2024
Conducting high-quality overviews of reviews (OoR) is time-consuming. Because the quality of systematic reviews (SRs) varies, it is necessary to critically appraise SRs when conducting an OoR. A well-established appraisal tool is A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2, which takes about 15-32 min per application. To save time,…
Descriptors: Decision Making, Time Management, Evaluation Methods, Quality Assurance
Mike Perkins; Jasper Roe; Binh H. Vu; Darius Postma; Don Hickerson; James McGaughran; Huy Q. Khuat – International Journal of Educational Technology in Higher Education, 2024
This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content modified to evade detection (n = 805). We compare these detectors to assess their reliability in identifying AI-generated text in educational settings, where they are increasingly used to address academic integrity…
Descriptors: Artificial Intelligence, Inclusion, Computer Software, Word Processing
Gal Raz; Sabrina Piccolo; Janine Medrano; Shari Liu; Kirsten Lydic; Catherine Mei; Victoria Nguyen; Tianmin Shu; Rebecca Saxe – Developmental Psychology, 2024
The study of infant gaze has long been a key tool for understanding the developing mind. However, labor-intensive data collection and processing limit the speed at which this understanding can be advanced. Here, we demonstrate an asynchronous workflow for conducting violation-of-expectation (VoE) experiments, which is fully "hands-off"…
Descriptors: Infants, Eye Movements, Attention, Expectation