Differences in motivation for biology learning: A measurement invariance testing and latent mean comparison approach

Anatomical Sciences Education · 2025-01-05 · 3 citations

Educational and psychological research often involves comparing motivation across groups. It is critical to ensure that observed differences in motivation are true variations by group, not due to measurement biases. With a diverse sample of undergraduate students (N = 2200), this study measured internal consistency and gathered validity evidence based on the internal structure of five motivation scales. To compare motivation for biology between groups of undergraduate students, this study tested for measurement scalar invariance by group and, accordingly, conducted latent factor mean comparisons to understand true group differences. On average, female students held lower expectancy beliefs and self-efficacy for biology learning than males. Female students perceived higher attainment value and utility value for biology learning and higher psychological cost. First-generation college students held lower expectancy beliefs and self-efficacy but perceived higher attainment value for biology learning than continuing-generation students. No differences in average motivation for biology learning were found between underrepresented racial minority (URM) and non-URM students. The implications of these findings and future research directions are also discussed.

Coding/categorizing of social data

Elsevier eBooks · 2025-01-01

Semantic Networks Extracted from Students’ Think-Aloud Data are Correlated with Students’ Learning Performance

2025-01-01

When students reflect on their learning from a textbook via think-aloud processes, network representations can be used to capture the concepts and relations from these data.What can we learn from the resulting network representations about students' learning processes, knowledge acquisition, and learning outcomes?This study brings methods from entity and relation extraction using classic and LLM-based methods to the application domain of educational psychology.We built a ground-truth baseline of relational data that represents relevant (to educational science), textbook-based information as a semantic network.Among the tested models, SPN4RE and LUKE achieved the best performance in extracting concepts and relations from students' verbal data.Network representations of students' verbalizations varied in structure, reflecting different learning processes.Correlating the students' semantic networks with learning outcomes revealed that denser and more interconnected semantic networks were associated with more elaborated knowledge acquisition.Structural features such as the number of edges and surface overlap with textbook networks significantly correlated with students' posttest performance.

More Expert-like Eye Gaze Movement Patterns are Related to Better X-ray Reading

ArXiv.org · 2025-05-10

Understanding how novices acquire and hone visual search skills is crucial for developing and optimizing training methods across domains. Network analysis methods can be used to analyze graph representations of visual expertise. This study investigates the relationship between eye-gaze movements and learning outcomes among undergraduate dentistry students who were diagnosing dental radiographs over multiple semesters. We use network analysis techniques to model eye-gaze scanpaths as directed graphs and examine changes in network metrics over time. Using time series clustering on each metric, we identify distinct patterns of visual search strategies and explore their association with students' diagnostic performance. Our findings suggest that the network metric of transition entropy is negatively correlated with performance scores, while the number of nodes and edges as well as average PageRank are positively correlated with performance scores. Changes in network metrics for individual students over time suggest a developmental shift from intermediate to expert-level processing. These insights contribute to understanding expertise acquisition in visual tasks and can inform the design of AI-assisted learning interventions.

WIP: Students’ Emotional and Study Strategies Responses to ECE Exam Success and Failure

2025-08-21

More Expert-Like Eye Gaze Movement Patterns are Related to Better X-ray Reading

Lecture notes in computer science · 2025-01-01

Learning from Illustrated Text: Is Generative Summarizing and Drawing Effective?

SSRN Electronic Journal · 2025-01-01

Does academic motivation relate to students’ use of problem-solving strategies in chemistry: a study of first-year college students / <i>¿Existe una relación entre la motivación académica y el uso de estrategias de resolución de problemas por parte de los estudiantes de Química? Un estudio con estudiantes universitarios de primer curso</i>

Journal for the Study of Education and Development Infancia y Aprendizaje · 2025-06-28

Research has explored various aspects of problem-solving strategies, including general processes, common mechanisms, influential factors and domain-specific applications. However, there has been limited investigation into the relationship between motivational factors such as self-efficacy and problem-solving strategies. The present study aimed to examine how motivational factors, including self-efficacy, self-concept, goal orientation and interest, relate to problem-solving strategies in the context of chemistry. A total of 28 undergraduate chemistry students participated in the study, completing a motivation survey and solving 10 chemistry questions while engaging in a think-aloud protocol. The verbalizations during their problem-solving process were transcribed and coded. Additionally, their problem-solving performance was evaluated through scoring. Correlations were conducted to explore the relationship between motivational factors, coded strategies and chemistry scores. Lag-sequential analysis was also performed to identify any significantly disproportionate transitions between strategies. The results show that students with higher chemistry self-efficacy are more likely to follow the strategies taught in class. Students with higher chemistry self-concept are more likely to apply correct concepts and knowledge. These results reveal how self-efficacy and self-concept help with problem-solving in specific perspectives. Instructors can support low self-efficacy and low self-concept students differently because they exhibit different patterns of using problem-solving strategies.

Board 405: The Stressors for Doctoral Students Questionnaire (SDSQ): Year 3 of an RFE Project on Understanding graduate Engineering Student Well-Being and Retention

2024-08-03

at Urbana-Champaign with a focus in

Applying Network Analysis to Think-Aloud and Eye-Tracking Data

2024-01-01 · 1 citations