Student motivation is a well-established predictor of academic engagement and achievement. Despite its importance, motivation is difficult to assess accurately, as it is shaped by multiple, overlapping constructs and contextual factors. This complexity continues to pose challenges for researchers and practitioners seeking measurement tools with valid and reliable scores. While open-ended responses provide meaningful information about students’ motivation, traditional human scoring is time-consuming, subject to inconsistencies, and not easily scalable. Advances in natural language processing, especially with transformer-based large language models, offer promising new approaches for automated scoring. However, their use in scoring student motivation assessments remains largely undocumented, and practical applications are in the early stages of development. This dissertation addresses this gap through two studies. The first study presents a scoping review of transformer-based approaches to motivation scoring, examining model types, scoring methods, target constructs, and available psychometric evidence. Guided by the PRISMA-ScR protocol, the review identified only nine studies, underscoring the limited research in this area. The second study empirically evaluates transformer models for motivation assessment, comparing fine-tuned encoder models (BERT, DeBERTa) with rubric-prompted decoder models (GPT-3.5 Turbo, GPT-4.1). Model performance is evaluated through a psychometric lens, including analyses of human–machine agreement, construct validity, subgroup fairness, and predictive validity with academic outcomes such as GPA and retention. Notably, DeBERTa outperformed human raters in predicting academic outcomes, suggesting that certain transformer models may capture motivational signals with greater predictive value—even when agreement with human scores is modest. However, validity analyses revealed important limitations: models demonstrated inconsistent construct validity and notable subgroup disparities, raising concerns about fairness. Overall, while transformer-based approaches, specifically DeBERTa, hold promise for scalable motivation assessment, challenges remain in ensuring interpretability, validity, and equity. This study also discusses the challenges and limitations encountered, outlines practical implications for educational assessment, and identifies directions for future research in developing robust and fair applications of transformer models.
The acetone-to-isobutene (ATIB) conversion is part of the ethanol cascade reaction to produce highly valuable compounds. Lewis acid sites can lead to selective C–C coupling and self-deoxygenation pathways in the acetone aldol condensation reaction. However, the reaction mechanism, nature of active sites, and the role of local environment are not well understood. This work demonstrates that well-dispersed isolated Ce atoms within the dealuminated BEA zeolite (CedeAlBEA) exhibit exceptional isobutene formation during the ATIB reaction by providing optimal Lewis acidity, which facilitates the direct decomposition of diacetone alcohol (DAA) to isobutene. In contrast, elevated cerium loadings lead to the formation of CeO2 nanoparticles, which favor side reactions such as DAA dehydration to mesityl oxide (MSO). In situ DRIFTS experiments with acetone adsorption reveal that adjacent silanol (Si–OH) groups in open Ce sites play an essential role in acetone activation, enabling the concerted adsorption of two acetone molecules, on the OH group and the Lewis active site, thus facilitating selective C–C bond formation and stabilizing the transition state for isobutene production. Kinetic assessments, including reactions with DAA as the reactant and kinetic isotope effect measurements, demonstrated that the direct decomposition of DAA to isobutene and acetic acid is the rate-limiting step. Accordingly, a Langmuir-Hinshelwood mechanism is proposed, involving the cooperative adsorption of two acetones molecules on isolated Ce species and the adjacent Si–OH groups. Building on these insights, bimetallic Ce–M catalysts were developed by introduction of a second metal with distinct electronic properties to enhance metal dispersion. In this system, the isolated Ce atoms serve as anchors for the second metal, generating dual Lewis acid sites. Combinations such as Ce–Ga and Ce–Sc preserved high dispersion and achieved 100% theoretical selectivity to isobutene (88.9% yield) even at high total metal loadings. These findings demonstrate that pairing confined Ce atoms with a secondary metal can overcome dispersion limitations, increase active site density, and mitigate metal aggregation, offering a novel strategy for the rational design of bifunctional zeolite catalysts for selective C–C coupling and deoxygenation reactions.
Abstract Coordinating joint actions requires participants to maintain moment-to-moment alignment as they progress through multiple tasks towards a shared goal. This creates the coordination problem of negotiating whether participants intend to continue to the next step in a task (i.e., make a horizontal transition) or shift to the next task (i.e., make a vertical transition). Language plays a central role in resolving this problem by enabling participants to distinguish horizontal and vertical transitions with specialised coordination markers (words like yeah, uh-huh, okay). Coordination markers constitute an important component of procedural coordination in adults; however, little is known about how children acquire the ability to use them. Here, we addressed this gap by investigating (1) how 4–8 year-old children speaking Swiss French and Vietnamese deploy coordination markers in peer interactions and (2) how the acquisition of these markers relates to the development of perspective-taking skills. In an experiment, we tested how N = 266 children and N = 158 adults from Switzerland and Vietnam navigated the joint task of LEGO model construction in visible (no barrier) and hidden (separated with a barrier) conditions. Our findings show that children acquire the ability to signal vertical transitions and the linguistic markers associated with them earlier than horizontal transitions. From early to middle childhood, there is a notable increase in both the frequency and diversity of coordination markers produced by children; however, their productivity remains limited compared to adults. Besides age, the acquisition of coordination markers is linked to the development of perspective-taking abilities, which enable children to flexibly adapt their use of coordination markers in response to changes in mutual visibility. Our study highlights how emerging socio-cognitive capacities support the acquisition of coordinating conventions across two typologically diverse languages.
Abstract Human social interactions display a complex choreography of dynamic, non-verbal signals such as nods and blinks. Yet, little is known about how these cues contribute to the detection of social contingency, i.e., how exactly does one know that two people are interacting with one another? To answer this question, we developed an experimental paradigm where observers had to recognize genuine and fake contingency in naturalistic, dyadic interactions. With two independent experiments (N = 206), we show that perception of contingency is robust even with severely degraded interactional stimuli and that observers causally rely on the link between a speaker’s speech and the listener’s motion. Crucially, inference about appropriate contingency is driven by temporally aligned, dynamic predictions rather than average quantity of movement or any lagged correlation between speech and motion. To model this perceptual process, we introduce the concept of a ‘social transfer function’: a pre-learned schema that generates predictions of a listener’s speech-contingent response and, based on how well-matched the predictions are to observed behaviour, is able to predict observer judgments of genuine contingency. Taken together, these results provide mechanistic insights into the audiovisual features that contribute to perception of social contingency, and open new ways to identify markers of contingency in people with disorders of consciousness, autism and social anxiety.
