Developmental patterns of children's shyness: Relations with physiological,emotional, and regulatory responses to being treated unfairly

The dysregulation of social fear has been widely studied in children's shyness, but we know little about how shy children regulate during unfair treatment. We first characterized developmental patterns of children's shyness (N = 304, n_girls = 153; 74% White, 26% Other) across 2 (M_age = 2.07), 3 (M_age = 3.08), 4 (M_age = 4.08), and 6 (M_age = 6.58) years of age. Data collection occurred from 2007 to 2014. At age 6, the high stable group had higher cardiac vagal withdrawal and lower expressed sadness and approach-related regulatory strategy than the low stable group when being treated unfairly. Although shy children may be more physiologically impacted by being treated unfairly, they may mask their sadness to signal appeasement.     

Beyond item analysis: Connecting student behaviour and performance using e-assessment logs

Traditional item analyses such as classical test theory (CTT) use exam-taker responses to assessment items to approximate their difficulty and discrimination. The increased adoption by educational institutions of electronic assessment platforms (EAPs) provides new avenues for assessment analytics by capturing detailed logs of an exam-taker's journey through their exam. This paper explores how logs created by EAPs can be employed alongside exam-taker responses and CTT to gain deeper insights into exam items. In particular, we propose an approach for deriving features from exam logs for approximating item difficulty and discrimination based on exam-taker behaviour during an exam. Items for which difficulty and discrimination differ significantly between CTT analysis and our approach are flagged through outlier detection for independent academic review. We demonstrate our approach by analysing de-identified exam logs and responses to assessment items of 463 medical students enrolled in a first-year biomedical sciences course. The analysis shows that the number of times an exam-taker visits an item before selecting a final response is a strong indicator of an item's difficulty and discrimination. Scrutiny by the course instructor of the seven items identified as outliers suggests our log-based analysis can provide insights beyond what is captured by traditional item analyses.

Practitioner notes

What is already known about this topic

• Traditional item analysis is based on exam-taker responses to the items using mathematical and statistical models from classical test theory (CTT). The difficulty and discrimination indices thus calculated can be used to determine the effectiveness of each item and consequently the reliability of the entire exam.

What this paper adds

• Data extracted from exam logs can be used to identify exam-taker behaviours which complement classical test theory in approximating the difficulty and discrimination of an item and identifying items that may require instructor review.

Implications for practice and/or policy

• Identifying the behaviours of successful exam-takers may allow us to develop effective exam-taking strategies and personal recommendations for students.
• Analysing exam logs may also provide an additional tool for identifying struggling students and items in need of revision.

     

Higher education strategy in digital transformation

Education and Information Technologies - Digital transformation in the global higher education industry determines the future roadmap to a sustainable education management strategy. This research...