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Xiong, Yao; Schunn, Christian D.; Wu, Yong – Journal of Computer Assisted Learning, 2023
Background: For peer assessment, reliability (i.e., consistency in ratings across peers) and validity (i.e., consistency of peer ratings with instructors or experts) are frequently examined in the research literature to address a central concern of instructors and students. Although the average levels are generally promising, both reliability and…
Descriptors: Peer Evaluation, Computer Assisted Testing, Test Reliability, Test Validity
Blaženka Divjak; Barbi Svetec; Damir Horvat – Journal of Computer Assisted Learning, 2024
Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic…
Descriptors: Automation, Formative Evaluation, Test Validity, Test Reliability
Yue Huang; Joshua Wilson – Journal of Computer Assisted Learning, 2025
Background: Automated writing evaluation (AWE) systems, used as formative assessment tools in writing classrooms, are promising for enhancing instruction and improving student performance. Although meta-analytic evidence supports AWE's effectiveness in various contexts, research on its effectiveness in the U.S. K-12 setting has lagged behind its…
Descriptors: Writing Evaluation, Writing Skills, Writing Tests, Writing Instruction
Kevin Ackermans; Marjoke Bakker; Pierre Gorissen; Anne-Marieke Loon; Marijke Kral; Gino Camp – Journal of Computer Assisted Learning, 2024
Background: A practical test that measures the information and communication technology (ICT) skills students need for effectively using ICT in primary education has yet to be developed (Oh et al., 2021). This paper reports on the development, validation, and reliability of a test measuring primary school students' ICT skills required for…
Descriptors: Test Construction, Test Validity, Measures (Individuals), Elementary School Students
Mohammad Nayef Ayasrah; Mohamad Ahmad Saleem Khasawneh; Mazen Omar Almulla; Amoura Hassan Aboutaleb – Journal of Computer Assisted Learning, 2025
Background: One area that has been dramatically changed by artificial intelligence (AI) is educational environments. Chatbots, Recommender Systems, Adaptive Learning Systems and Large Language Models have been emerging as practical tools for facilitating learning. However, using such tools appropriately is challenging. In this regard, the…
Descriptors: Test Construction, Test Validity, Test Reliability, Rating Scales
Ali Alqarni – Journal of Computer Assisted Learning, 2025
Background: Critical thinking is essential in modern education, and artificial intelligence (AI) offers new possibilities for enhancing it. However, the lack of validated tools to assess teachers' AI-integrated pedagogical skills remains a challenge. Objectives: The current study aimed to develop and validate the Artificial Intelligence-Critical…
Descriptors: Artificial Intelligence, Technology Uses in Education, Test Construction, Test Validity
Andersen, Martin S.; Makransky, Guido – Journal of Computer Assisted Learning, 2021
Measuring cognitive load is important in virtual learning environments (VLE). Thus, valid and reliable measures of cognitive load are important to support instructional design in VLE. Through three studies, we investigated the validity and reliability of Leppink's Cognitive Load Scale (CLS) and developed the extraneous cognitive load (EL)…
Descriptors: Test Construction, Test Validity, Test Reliability, Cognitive Processes
Hewson, Claire; Charlton, John P. – Journal of Computer Assisted Learning, 2019
The use of e-assessment methods raises important concerns regarding the reliability and validity of these methods. Potential threats to validity include mode effects and the possible influence of computer-related attitudes. Although numerous studies have now investigated the validity of online assessments in noncourse-based contexts, few studies…
Descriptors: Computer Assisted Testing, Test Reliability, Test Validity, College Students
Wafa Mohammed Aldighrir; Fatima's Mohamed Asiri – Journal of Computer Assisted Learning, 2025
Background: As educational institutions increasingly operate as multicultural hubs, leaders must navigate the complexities of cultural differences, language barriers and diverse learning styles in digital environments. These challenges are amplified by the lack of non-verbal cues and the asynchronous nature of online communication, which can lead…
Descriptors: Foreign Countries, Test Construction, Measures (Individuals), Test Validity
Patael, Smadar; Shamir, Julia; Soffer, Tal; Livne, Eynat; Fogel-Grinvald, Haya; Kishon-Rabin, Liat – Journal of Computer Assisted Learning, 2022
Background: The global COVID-19 pandemic turned the adoption of on-line assessment in the institutions for higher education from possibility to necessity. Thus, in the end of Fall 20/21 semester Tel Aviv University (TAU)--the largest university in Israel--designed and implemented a scalable procedure for administering proctored remote…
Descriptors: COVID-19, Pandemics, Computer Assisted Testing, Foreign Countries
Hooker, J. F.; Denker, K. J.; Summers, M. E.; Parker, M. – Journal of Computer Assisted Learning, 2016
Previous research into the benefits student response systems (SRS) that have been brought into the classroom revealed that SRS can contribute positively to student experiences. However, while the benefits of SRS have been conceptualized and operationalized into a widely cited scale, the validity of this scale had not been tested. Furthermore,…
Descriptors: Technology Uses in Education, Factor Analysis, Audience Response Systems, Handheld Devices
Chang, Wen-Hui; Liu, Yuan-Chen; Huang, Tzu-Hua – Journal of Computer Assisted Learning, 2017
The purpose of this study is to develop a multi-dimensional scale to measure students' awareness of key competencies for M-learning and to test its reliability and validity. The Key Competencies of Mobile Learning Scale (KCMLS) was determined via confirmatory factor analysis to have four dimensions: team collaboration, creative thinking, critical…
Descriptors: Test Construction, Multidimensional Scaling, Electronic Learning, Test Reliability
Cheng, M.-T.; She, H.-C.; Annetta, L. A. – Journal of Computer Assisted Learning, 2015
Many studies have shown the positive impact of serious educational games (SEGs) on learning outcomes. However, there still exists insufficient research that delves into the impact of immersive experience in the process of gaming on SEG-based science learning. The dual purpose of this study was to further explore this impact. One purpose was to…
Descriptors: Science Instruction, Educational Games, Technology Uses in Education, Educational Technology
Uzunboylu, H.; Ozdamli, F. – Journal of Computer Assisted Learning, 2011
Successful integration of mobile learning (m-learning) technologies in education primarily demands that teachers' perception of such technologies should be determined. Therefore, the perceptions of teachers are of great significance. There is no available instrument that assesses teachers' perceptions of m-learning. Our research provided the first…
Descriptors: Electronic Learning, Feedback (Response), Test Validity, Measures (Individuals)

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