The release of ChatGPT in 2022 has generated extensive speculation about how Artificial Intelligence (AI) will impact the capacity of institutions for higher learning to achieve their central missions of promoting learning and certifying knowledge. Our main questions were whether people could identify AI-generated text and whether factors such as…

Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…

Evidence from fMRI research indicates that individual creative thinking ability -- defined as performance on divergent thinking tasks, subjectively assessed by human raters -- can be predicted based on the strength of functional connectivity (FC) between the brain's default mode network (DMN) and frontoparietal control network (FPCN). Here, we…

Arai et al. (2007) showed that structural priming in the comprehension of English dative sentences only occurred when the verb was repeated between prime and target, suggesting a lexically-dependent mechanism of structure prediction. However, a recent study in Mandarin comprehension found abstract (verb-independent) structural priming and such…

Electrophysiology studies have identified two event-related potentials that are modulated by predictive processes during language comprehension: the N400 and a frontal positivity. The N400 is smaller when words are presented within highly restrictive sentences, indicating reduced lexical retrieval costs. Violations of strong predictions generate…

Game-based learning environments hold significant promise for facilitating learning experiences that are both effective and engaging. To support individualised learning and support proactive scaffolding when students are struggling, game-based learning environments should be able to accurately predict student knowledge at early points in students'…

Structural priming studies in production have demonstrated stronger priming effects for unexpected sentence structures (inverse preference effect). This is consistent with error-based implicit learning accounts that assume learning depends on prediction error. Such prediction error can be verb-specific, leading to strong priming when a verb that…

Sentiment Analysis (SA), a technique based on applying artificial intelligence to analyze textual data in natural language, can help to characterize interactions between students and teachers and improve learning through timely, personalized feedback, but its use in education is still scarce. This systematic literature review explores how SA has…

This study examines the extent to which instructions to self-explain vs. "other"-explain a text lead readers to produce different forms of explanations. Natural language processing was used to examine the content and characteristics of the explanations produced as a function of instruction condition. Undergraduate students (n = 146)…

A number of studies have found evidence for the so-called "ambiguity advantage," that is, faster processing of ambiguous sentences compared with unambiguous counterparts. While a number of proposals regarding the mechanism underlying this phenomenon have been made, the empirical evidence so far is far from unequivocal. It is compatible…

This study aims to evaluate the effectiveness and potential utility of using machine learning and natural language processing techniques to develop models that can reliably predict the relative difficulty of incoming chat reference questions. Using a relatively large sample size of chat transcripts (N = 15,690), an empirical experimental design…

This study examines whether second language (L2) learners predict upcoming language prior to the verb in Japanese. Taking the dependency involving negative polarity adverbs -- "zenzen" 'at all' and "amari" '(not) very' -- as a test case, this study examined whether Japanese native speakers and L2 learners of Japanese, aided by…

In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…

Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…

Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…