Core executive functions are selectively related to different facets of motor competence in preadolescent children

Background: Although accumulating evidence suggests that motor and cognitive development is interrelated, only a few studies have investigated links between executive function and motor control. Therefore, the present cross-sectional study examined the relationship between motor competences and core components of executive functioning, including inhibitory control, working memory and cognitive flexibility. Methods: In 89 preadolescent children, motor competences were assessed using the MOBAK-5 test battery. Additionally, all participants completed computer-based versions of the Flanker task, which included standard and switch blocks, and the 2-Back task. Results: Partial correlations (correcting for age, gender and body mass index) revealed that locomotor skills were associated with the adjusted hit-rate on the 2-Back task (r?=?0.34) whereas object control was linked with conflict score on the Flanker task (r?=??0.39). In contrast, there was no correlation between switch costs and motor competences. Conclusion: In preadolescent children, high competences in locomotor skills and object control skills are associated with high performance on specific executive function tasks. This finding supports the current view that motor competences and cognitive control share some common underlying processes.     

Dealing with errors in mathematics classrooms: Structure and relevance of perceived error climate

Errors are often perceived by students as self-threatening and not as learning opportunities. The present work focuses on contextual influences on reactions to errors and learning processes. Based on prior research, a conceptualization of perceived error climate in the classroom with eight subdimensions and one superordinate uniform factor is proposed and a newly developed student questionnaire for its assessment is presented. Results of a study with N = 1116 students from 56 mathematics classrooms in German secondary schools indicated the validity of the error climate conceptualization and the suitability of the questionnaire. Moreover, the results showed that perceived error climate in the classroom predicted the adaptivity of students’ individual reactions to errors above and beyond perceived classroom goal structures and personal achievement motivation (academic self-concept, mastery goal orientation). In addition, the study provided evidence that perceived error climate affects – partially mediated through students’ individual reactions to errors – the quantity and self-regulation of students’ effort.     

Academic engagement: A review of the literature 2011-2019

We provide a systematic review of the literature on academic engagement from 2011 onwards, which was the cut-off year of a previous review article published in Research Policy. Academic engagement refers to knowledge-related interactions of academic scientists with external organisations. It includes activities such as collaborative research with industry, contract research, consulting and informal ties. We consolidate what is known about the individual, organisational and institutional antecedents of academic engagement, and its consequences for research, commercialisation, and society at large. Our results suggest that individual characteristics associated with academic engagement include being scientifically productive, senior, male, locally trained, and commercially experienced. Academic engagement is also socially conditioned by peer effects and disciplinary characteristics. In terms of consequences, academic engagement is positively associated with academics’ subsequent scientific productivity. We propose new areas of investigation where evidence remains inconclusive, including individual life cycle effects, the role of organisational contexts and incentives, cross-national comparisons, and the impact of academic engagement on the quality of subsequent research as well as the educational, commercial and society-wide impact.     

Situated mathematics teaching within electrical engineering courses

The initial phase of undergraduate engineering degree programmes often comprises courses requiring mathematical expertise which in some cases clearly exceeds school mathematics, but will be imparted only later in mathematics courses. In this article, an approach addressing this challenge by way of example within a fundamentals of electrical engineering course is presented. The concept focuses on gaining specific mathematical knowledge and competencies in the technical context of this course. For this purpose, a complementary blended learning scenario centring around a web-based learning platform and involving an adaptation of the course was developed. The concept particularly considers the heterogeneity of today's student groups and is discussed with regard to related approaches, didactical considerations, and technical implementation. For the interventions, the results of a questionnaire-based evaluation proving students' acceptance and positive influence on examination performance are presented.     

Using virtual microscopy to scaffold learning of pathology: a naturalistic experiment on the role of visual and conceptual cues

New representational technologies, such as virtual microscopy, create new affordances for medical education. In the article, a study on the following two issues is reported: (a) How does collaborative use of virtual microscopy shape students’ engagement with and learning from virtual slides of tissue specimen? (b) How do visual and conceptual cues scaffold students’ reasoning? Fifteen pairs of medical students participated in two sessions in which the students used a virtual microscope as a diagnostic tool in the context of learning pathology. The slides provided the students with varying levels of visual and conceptual cueing. The sessions were videotaped, and the students’ reasoning while using the microscope was analysed. The students’ written answers were analysed in terms of the findings they made and the diagnoses suggested. At a general level, the results show that students engage actively in this kind of virtually-mediated environment. The visual and/or conceptual cues improve students’ performance, and guide the students’ perception and reasoning in a manner that is productive from the point of view of learning to make clinically relevant observations. Scaffolding students’ reasoning process through cues furthermore assists the students in avoiding the most obvious pitfalls such as overlooking critical areas of a specimen. Overall, visual and conceptual cues improve students’ reasoning in perceptual and cognitive terms, while still allowing space for the making of “relevant mistakes” that may further the students’ diagnostic skills.     

Computer-based learning of spelling skills in children with and without dyslexia

Our spelling training software recodes words into multisensory representations comprising visual and auditory codes. These codes represent information about letters and syllables of a word. An enhanced version, developed for this study, contains an additional phonological code and an improved word selection controller relying on a phoneme-based student model. We investigated the spelling behavior of children by means of learning curves based on log-file data of the previous and the enhanced software version. First, we compared the learning progress of children with dyslexia working either with the previous software (n = 28) or the adapted version (n = 37). Second, we investigated the spelling behavior of children with dyslexia (n = 37) and matched children without dyslexia (n = 25). To gain deeper insight into which factors are relevant for acquiring spelling skills, we analyzed the influence of cognitive abilities, such as attention functions and verbal memory skills, on the learning behavior. All investigations of the learning process are based on learning curve analyses of the collected log-file data. The results evidenced that those children with dyslexia benefit significantly from the additional phonological cue and the corresponding phoneme-based student model. Actually, children with dyslexia improve their spelling skills to the same extent as children without dyslexia and were able to memorize phoneme to grapheme correspondence when given the correct support and adequate training. In addition, children with low attention functions benefit from the structured learning environment. Generally, our data showed that memory sources are supportive cognitive functions for acquiring spelling skills and for using the information cues of a multi-modal learning environment.     

Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments.

Practitioner notes

What is already known about this topic

• There is considerable research in educational science on peer-feedback processes.
• Natural language processing facilitates the analysis of students' textual data.
• There is a lack of systematic orientation regarding which NLP techniques can be applied to which data to effectively support the peer-feedback process.

What this paper adds

• A comprehensive overview model that describes the relevant activities and products in the peer-feedback process.
• A terminological and procedural scheme for designing NLP-based adaptive support measures.
• An application of this scheme to the peer-feedback process results in exemplifying the use cases of how NLP may be employed to support each learner activity during peer-feedback.

Implications for practice and/or policy

• To boost the effectiveness of their peer-feedback scenarios, instructors and instructional designers should identify relevant leverage points, corresponding support measures, adaptation targets and automation goals based on theory and empirical findings.
• Management and IT departments of higher education institutions should strive to provide digital tools based on modern NLP models and integrate them into the respective learning management systems; those tools should help in translating the automation goals requested by their instructors into prediction targets, take relevant data as input and allow for evaluating the predictions.