Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…

This study employs advanced data mining techniques to investigate the DASS-42 questionnaire, a widely used psychological assessment tool. Administered to 680 students at Necmettin Erbakan University's Ahmet Kelesoglu Faculty of Education, the DASS-42 comprises three distinct subscales--depression, anxiety and stress--each consisting of 14 items.…

Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…

The rapid development of artificial intelligence has driven the transformation of educational evaluation into big data-driven. This study used a systematic literature review method to analyzed 44 empirical research articles on the evaluation of big data education. Firstly, it has shown an increasing trend year by year, and is mainly published in…

High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…

Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…

Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…

Automatic item generation may supply many items instantly and efficiently to assessment and learning environments. Yet, the evaluation of item quality persists to be a bottleneck for deploying generated items in learning and assessment settings. In this study, we investigated the utility of using large-language models, specifically Llama 3-8B, for…

In this article, we adopt culturally relevant perspectives on developmental science that acknowledge and value the diversity of backgrounds and experiences of young children and their families to identify opportunities to advance the measurement of early childhood development. We focus on direct child assessments that can drive more equitable…

Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS…

The world has experienced rapid changes, leading to pressing issues such as environmental degradation, social inequality, and resource depletion. As a transdisciplinary field, evaluation has emerged as a crucial tool in addressing these challenges and promoting systemic change. However, concerns have been raised regarding the field's capacity to…

To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…

With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate "Instructional Support" domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning…

Peer assessment has proven to be a useful strategy for increasing the timeliness and quantity of formative feedback, as well as for promoting metacognitive thinking among students. Previous research has determined that reviews that contain suggestions can motivate students to revise and improve their work. This paper describes a method for…

Debates surrounding the use of data science in educational AI are frequently rather entrenched, revolving around commercial models and talk of teacher replacement. This article explores the potential for digital textual analysis within humanities and social science education, advocating for a sociologically-driven approach that complements, rather…