This case study explores the use of large language models (LLMs) as analytical partners for data exploration and interpretation. Grounded in original research, it navigates the intricacies of using LLMs for uncovering themes from datasets. The study tackles various methodological and practical challenges encountered during the research process…

Certification organizations aim to assess candidates on their breadth and depth of knowledge to determine eligibility for certification in their field of specialty. Assessments used for certification, when appropriately constructed, should use questions (or items) that assess the entirety of the field. However, comparing the plethora of the…

Biblical didactics is an important element of confessional religious education. In traditional settings, it is primarily associated with working with the text, alone or in groups, in plenary discussion or pantomime. Nowadays, however, young people are increasingly acquiring their knowledge--including about the Bible--on the Internet, using new…

Computational models of infant word-finding typically operate over transcriptions of infant-directed speech corpora. It is now possible to test models of word segmentation on speech materials, rather than transcriptions of speech. We propose that such modeling efforts be conducted over the speech of the experimental stimuli used in studies…

The phenomenon of scalar diversity refers to the well-replicated finding that different scalar expressions give rise to scalar implicatures (SIs) at different rates. Previous work has shown that part of the scalar diversity effect can be explained by theoretically motivated factors. Although the effect has been established only in controlled…

A significant body of recent research in the field of Learning Analytics has focused on leveraging machine learning approaches for predicting at-risk students in order to initiate timely interventions and thereby elevate retention and completion rates. The overarching feature of the majority of these research studies has been on the science of…

Prediction-based accounts of language acquisition have the potential to explain several different effects in child language acquisition and adult language processing. However, evidence regarding the developmental predictions of such accounts is mixed. Here, we consider several predictions of these accounts in two large-scale developmental studies…

Previous studies on L2 (i.e., second language) Chinese compound processing have focused on the relative efficiency of two routes: holistic processing versus combinatorial processing. However, it is still unclear whether Chinese compounds are processed with multilevel representations among L2 learners due to the hierarchical structure of the…

Eventualities have been recognized as psychologically and linguistically relevant for more than 50 years. Psychologically, eventualities are complex bundles of information derived from our perceptions of the world. The question for linguists is how much of this complexity is reflected in our eventuality-denoting lexical entries and the…

Recent studies have demonstrated that saccadic programming in reading is not only determined by low-level visual factors. High-level morphological effects on saccade have been shown in two morphologically rich languages. In the present study, we examined the underlying mechanism of such morphological influences by comparing the processes of…

How do infants learn about the formal properties of language using only cues they can access in speech? And what intuitions do they bring to the learning problem? Chapter 2: To explore whether current notions of statistically-based language learning could successfully scale to infants' linguistic experiences "in the wild", we implemented…

Recent years have seen increased interests in applying the latest technological innovations, including artificial intelligence (AI) and machine learning (ML), to the field of education. One of the main areas of interest to researchers is the use of ML to assist teachers in assessing students' work on the one hand and to promote effective…

This study investigates the potential of using ChatGPT as a teachable agent to support students' learning through teaching, specifically in programming education. While learning by teaching (LBT) is an effective pedagogical strategy, traditional teachable agents often struggle with facilitating dynamic, dialogue-based interactions. Our research…

Previous research suggests that statistical learning enhances memory for self-related information at the individual level and that individuals exhibit better memory for partner-related items than they do for irrelevant items in joint contexts (i.e., the joint memory effect, JME). However, whether statistical learning improves memory for…

This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…