Artificial intelligence (AI) technologies, especially language models like ChatGPT, are revolutionizing academic writing by generating human-like text and supporting thesis development. While some research explores ChatGPT in academic writing, none compares the experiences of young researchers using AI for the first time versus non-users in their…

The benefits of Generative Artificial Intelligence (GenAI) in enhancing second language (L2) learning are well established. However, these advantages can only be realised if learners are willing to adopt the technology. This study, grounded in the Theory of Planned Behaviour (TPB), investigated the factors influencing the behavioural intention to…

Artificial intelligence (AI) is increasingly exploited to promote student engagement. This study combined topic modelling, keyword analysis, trend test and systematic analysis methodologies to analyse AI-supported student engagement (AIsE) studies regarding research keywords and topics, AI roles, AI systems and algorithms, methods and domains,…

This study explores the integration of generative artificial intelligence (AI) into qualitative research within a higher education context. Through a collaborative self-study, a doctoral candidate and their dissertation supervisor examined the application of Google's Gemini 1.5 to analyze interview data from a dissertation of practice (DiP)…

Purpose: This research examines the complex relationship between usage of Chat Generative Pre-Trained Transformer (ChatGPT) amongst student and their creativity, learning and assessment using empirical data collected from postgraduate students. In addition, the study explores the student's intrinsic motivation for usage to understand student…

We report four experiments investigating the effect of prosody on listening comprehension in 11-13-year-old children. Across all experiments, participants listened to short object descriptions and answered content-based questions about said objects. In Experiments 1-3, the descriptions were read in an emotionally positive or neutral tone of voice.…

The increasing popularity of digital textbooks as a new learning media has resulted in a growing interest in developing a new generation of "adaptive textbooks" that can help readers to learn better through adapting to the readers' learning goals and the current state of knowledge. These adaptive textbooks are most frequently powered by…

Among all the learning resources within MOOCs such as video lectures and homework, the discussion forum stood out as a valuable platform for students' learning through knowledge exchange. However, peer interactions on MOOC discussion forums are scarce. The lack of interactions among MOOC learners can yield negative effects on students' learning,…

In this digital age, there is an abundance of online educational materials in public and proprietary platforms. To allow effective retrieval of educational resources, it is a necessity to build keyword-based search engines over these collections. In modern Web search engines, high-quality rankings are obtained by applying machine learning…

We explore how different components of an Automatic Short Answer Grading (ASAG) model affect the model's ability to generalize to questions outside of those used for training. For supervised automatic grading models, human ratings are primarily used as ground truth labels. Producing such ratings can be resource heavy, as subject matter experts…

Today, there is a vast amount of online material for learners. However, due to the lack of prerequisite information needed to master them, a lot of time is spent in identifying the right learning content for mastering these concepts. A system that captures underlying prerequisites needed for learning different concepts can help improve the quality…

Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…

To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not…

We present the results of an ongoing collaboration between computer science and psychology researchers that employs Natural Language Processing (NLP) methods to examine the trajectory of semantic space used during group idea generation sessions. Specifically, we track and estimate the region of semantic space being used and the degree to which new…

Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…