Instructional Science

Linguistic demands of instructions: Effects on students’ expectancy-value beliefs

2 months 3 weeks ago
Language in educational contexts is characterized by complex and cognitively demanding features that can be challenging to use. Based on situated expectancy-value theory (SEVT), we assumed that these linguistic demands can lower students’ expectancies of performing well and the intrinsic value they place on tasks. This is particularly true of students with lower language abilities. Consequently, they may be less motivated to actively engage in academic tasks, potentially leading to lower academic achievement. To test this assumption, we linguistically varied an instructional statistics video into three conditions (easy, moderate, and difficult) and randomly assigned a total of 123 pre-service teachers to each condition. We measured their expectancies of success and intrinsic task value halfway through the instructional video and conducted an achievement test after the instruction. Drawing on path analysis, our results showed that different linguistic conditions had no significant effect on the students’ expectancy-value beliefs. However, we found a significant positive effect of language ability and a significant negative effect of the interaction between the linguistically difficult instruction and language ability on expectancies of success. Contrary to our expectations, this indicates that high linguistic difficulty is associated with lower expectancies of success among students with increasing language abilities. Nevertheless, this finding emphasizes the importance of considering the fit between contextual and individual features. However, it did not have an indirect effect on student achievement. The findings are further discussed, highlighting their implications for future research and delineating linguistic design in educational contexts.

Half a century of Instructional Science: a bibliometric analysis

2 months 3 weeks ago
Instructional Science is a prominent international journal of learning sciences. This article provides a comprehensive bibliometric overview of the major trends within the journal from 1972 to 2023. The study focuses on assessing the journal’s impact, identifying the most productive and influential authors, institutions, and countries, as well as analysing the evolution of key topics over time. The primary source of bibliometric data for this analysis is the Scopus scientific database. Some information of the Web of Science Core Collection database is retrieved in specific instances to enhance the analysis. Additionally, the paper includes a graphical mapping of the bibliographic data using VOS viewer software, which provides more in-depth analysis through co-citation, bibliographic coupling, and co-occurrence of author keywords. The findings highlight the journal’s significant growth and impact over the years, and it is anticipated that it will continue to expand its international reach.