Data

An essential first step to implement a control strategy against herbivorous insects is the monitoring of their populations. The efficacy of pheromone-based traps in capturing herbivorous insects can be enhanced by adding adjuvants and using slow-release dispensers to ensure long-lasting attractiveness. Here, we present datasets from a two-year field monitoring campaign of the invasive brown marmorated stink bug, Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), using clear sticky traps baited with its aggregation pheromone and a synergist, tested towards different dispensers and adjuvants. Bycatch data for native stink bugs (all Hemiptera: Pentatomidae) and leaf-footed bugs (Hemiptera: Coreidae) are also presented. The R code provided was used to organize data and generate weekly captures or weekly density of both H. halys and non-target species. The information provided in this article may contribute to the optimization of pest control strategies in agriculture.

Constructed-response items offer rich evidence of writing proficiency, but the linguistic signals they contain vary with grade level. This study presents a cross-sectional analysis of 5638 English Language Arts essays from Grades 6–12 to identify which linguistic features predict proficiency and to characterize how their importance shifts across grade levels. We extracted a suite of lexical, syntactic, and semantic-cohesion features, and evaluated their predictive power using an interpretive dual-model framework combining LASSO and XGBoost algorithms. Feature importance was assessed through LASSO coefficients, XGBoost Gain scores, and SHAP values, and interpreted by isolating both consensus and divergences of the three metrics. Results show moderate, generalizable predictive signals in Grades 6–8, but no generalizable predictive power was found in the Grades 9–12 cohort. Across the middle grades, three findings achieved strong consensus. Essay length, syntactic density, and global semantic organization served as strong predictors of writing proficiency. Lexical diversity emerged as a key divergent feature, it was a top predictor for XGBoost but ignored by LASSO, suggesting its contribution depends on interactions with other features. These findings inform actionable, grade-sensitive feedback, highlighting stable, diagnostic targets for middle school while cautioning that discourse-level features are necessary to model high-school writing.

Advancements in data storage and data processing technologies has compelled higher education institutions to optimise the use of their data. Many universities globally have begun to implement learning analytics at their institutions to better understand and improve teaching and learning. African higher education institutions have been slow to implement learning analytics despite the continued accumulation of digital data. The research related to this study presents a dataset of Information Systems and Technology (IS&T) students from the University of KwaZulu-Natal, a South African university. The dataset comprises approximately 14,000 registered student records from 10 IS&T courses, primarily consisting of demographic data, academic performance (including past IS&T courses and school records), and Learning Management System (LMS) interaction data. The dataset exhibits an imbalance, characterised by a higher proportion of students who have successfully completed courses compared to those who have not. The dataset will be of interest to researchers engaged in learning analytics application studies, including early pass/fail prediction and grade classification, as well as those who want to test their techniques on a real-world dataset.