Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…

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…

Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…

Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…

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…

Background: In this technologically advanced era, media literacy is necessary to effectively evaluate the information and understand various biases inherent in media messages. Several media literacy (ML) tools are available; however, we need generic and objective tools that can be applied to all forms of media messages. Objectives: The current…

Background Study: Assessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education. Objectives: The present study evaluated the SSI…

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…

Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…

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…

Background: Computerised adaptive tests (CATs) are tests that provide personalised, efficient and accurate measurement while reducing testing time, depending on the desired level of precision. Schools have different types of assessments that can benefit from a significant reduction in testing time to varying degrees, depending on the area of…

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…

Background: Digital-first assessments leverage the affordances of technology in all elements of the assessment process--from design and development to score reporting and evaluation to create test taker-centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and…

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…