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: Integrating information from multiple sources is a common yet challenging learning task for secondary school students. Many underuse metacognitive skills, such as monitoring and control, which are essential for promoting engagement and effective learning outcomes. Objective: This study aims to examine the relationship between…

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: 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: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…

Background: Providing students with information on their current performance could help them improve by stimulating their reflection, but negative feedback that saliently mirrors task-related failure can harm motivation. In the context of automated scoring based on artificial intelligence, we explored how feedback on written texts might be…

Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…

Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…

Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…

Background: The recent advent of powerful, exam-passing large language models (LLMs) in public awareness has led to concerns over students cheating, but has also given rise to calls for including or even focusing education on LLMs. There is a perceived urgency to react immediately, as well as claims that AI-based reforms of education will lead to…

Background: While automatic speech recognition (ASR) is increasingly used for commercial purposes, its influence on the learners' linguistic performance in terms of oral complexity, accuracy and fluency was under-explored. To date, few studies have been conducted to investigate how the dictation ASR technology could be incorporated into language…

Background: Automated Writing Evaluation (AWE) systems to aid writing learning and instruction in primary and secondary education are growing increasingly popular. However, their effectiveness is hardly known. We conducted a systematic review focusing on the effects of these systems providing writing feedback to students in school settings.…

Background: Educational assessments increasingly shift towards computer-based formats. Many studies have explored how different types of automated feedback affect learning. However, few studies have investigated how digital performance feedback affects test takers' ratings of affective-motivational reactions during a testing session. Method: In…

Background: Developments in educational technology and learning analytics make it possible to automatically formulate and deploy personalized formative feedback to learners at scale. However, to be effective, the motivational and emotional impacts of such automated and personalized feedback need to be considered. The literature on feedback…

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…