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In this randomized control study, we evaluated science teachers' pedagogical practices via classroom observations following ongoing, intensive, and structured instructional support sessions. These sessions included virtual professional development (VPD) and virtual mentoring and coaching (VMC) that accompanied a literacy-infused science curriculum. Using a low-inference observational instrument, we explored the direct impact of VPD and VMC on fifth-grade science teachers' observed time allocation in a randomized controlled trial (RCT) validation study. The observations were collected three times during science instruction from 121 teachers in 68 schools from 35 public school districts in the U.S. state of Texas, during the 2017-2018 school year. Preliminary findings revealed pedagogical differences in time allocation among teachers between treatment and control classrooms. We identified improved instructional practices within treatment classrooms, which suggests the intervention had a positive effect by enhancing the quality of pedagogy as well as the content-area instruction in science.

Individuals with intellectual disabilities need an affective and sexual education adapted to their characteristics. There are few interventions that meet these objectives and offer empirical evidence of their efficacy. To respond to the limitations of existing interventions, an evidence-based affective-sexual educational intervention for adults with a mild degree of intellectual disability is proposed: SALUDIVERSEX. Participants will be randomly assigned to an intervention group that will receive the SALUDIVERSEX program or to a waiting list group. The intervention will be implemented by educators of occupational centers after a thorough training phase. Our main hypothesis is that the SALUDIVERSEX program will improve the sexual health and quality of life, through the joint action built into three components: the acquisition of basic information, the development of skills and strategies and the achievement of healthy attitudes towards the experience and expression of sexuality. The results of this approach could have important implications for optimizing the quality of life and self-determination of individuals with Intellectual disability by contributing to the development of healthy sexuality.

Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported collaborative learning (CSCL) setting. Exploring what types of feedback are used, and how they relate to each other and are related to academic performance has important implications for students and teachers. Methods: This study was conducted in the higher education setting. It used a dataset consisting of student peer feedback messages (N = 2444) and grades from 231 students who participated in a large engineering course. Using qualitative methods, peer feedback was coded inductively. Epistemic network analysis (ENA) was used to analyse the relation between peer feedback types and performance. Results: Based on the five types of peer feedback (i.e., 'management', 'cognition' 'affect', 'interpersonal factors' and 'suggestions for improvements'), the results of the ENA showed that student feedback categories 'management', 'cognition' and 'affect' were positively related to student performance at the formative assessment phase. Conclusions: The findings and the ENA visualizations also show that 'suggestions for improvement' and 'interpersonal factors' were not a significant part of student learning in peer assessment and feedback in the studied context.

There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing, analyzing, and presenting such data. As a result, school leaders, teachers, and students do not capitalize on the possibility of making decisions based on data. This is a serious barrier to the improvement of work in schools, teacher and student progress, and the development of effective Educational Technology (EdTech) products and services. Data standards can be used as a protocol on how different IT systems communicate with each other. When working with data from different public and private institutions simultaneously (e.g., different municipalities and EdTech companies), having a trustworthy data pipeline for retrieving the data and storing it in a secure warehouse is critical. In this study, we propose a technical solution containing a data pipeline by employing a secure warehouse--the Swedish University Computer Network (SUNET), which is an interface for information exchange between operational processes in schools. We conducted a user study in collaboration with four municipalities and four EdTech companies based in Sweden. Our proposal involves introducing a data standard to facilitate the integration of educational data from diverse resources in our SUNET drive. To accomplish this, we created customized scripts for each stakeholder, tailored to their specific data formats, with the aim of merging the students' data. The results of the first four steps show that our solution works. Once the results of the next three steps are in, we will contemplate scaling up our technical solution nationwide. With the implementation of the suggested data standard and the utilization of the proposed technical solution, diverse stakeholders can benefit from improved management, transportation, analysis, and visualization of educational data.

Identifying mathematically gifted students is an important objective in mathematics education. To describe skills typical of these students, researchers pose problems in several mathematical domains whose solutions require using different mathematical capacities, such as visualization, generalization, proof, creativity, etc. This paper presents an analysis of the solutions to two problems by 75 students (aged 11-14), as part of the selection test for a workshop to stimulate mathematical talent. These problems require the use of the capacity for mathematical generalization of solution methods. We define a set of descriptors of such capacity, use them to analyze students' solutions, and evaluate how well students with high capacity for generalization can be distinguished from average students. The results indicate that the two problems are suitable for identifying potential mathematically gifted students and several descriptors have high discriminatory power to identify students with high or low capacity for generalization.

Research into mathematics education at university level includes a wide range of theoretical approaches. This poses considerable challenges to researchers in terms of understanding and harmonizing the compatibility and commensurability of those approaches. The research community has already problematised and studied these challenges using networking theories. The networking theories framework is taken as a starting point in this study to contrast different approaches and to broaden the comparison of different frameworks. In particular, three case studies framed in the Action, Process, Object, Schema Theory, in the Problem-Solving approach, and in the Anthropological Theory of the Didactic are analysed. The differences and possible similarities between the three with regard to the research questions addressed, their objects of study, their empirical bases, as well as their research ends are considered. The analysis offers an insight into the potential for collaboration and the networking of theories in the field of university mathematics education.

Technology is increasingly being integrated into classrooms worldwide to enhance learning outcomes, and simulation technologies are becoming more popular to create realistic scenarios in controlled academic settings. However, simulation studies in agricultural education have been limited, making it difficult to assess the impact of simulation technologies on student learning. To address this literature gap, a systematic literature review of 17 articles was conducted to examine the use of simulation technology in agricultural education. The analysis revealed that simulation technologies were most used in agricultural science sub-disciplines that involve experimentation and practical application. Most studies focused on undergraduates and utilized quantitative research methods, with virtual and augmented reality being the most commonly employed types of simulation. Positive effects of simulation on learning outcomes were reported in most studies, including improved academic achievement, psychological factors such as anxiety, and tracking students' progress. However, the technology's time-consuming nature and potential for uncomfortable physical conditions like cybersickness were identified as demerits. More rigorous standards were recommended to improve reporting procedures in agricultural education studies with simulation technologies.

We present a case study of proving by three 12-13-year-old students with different levels of mathematical giftedness. After analysing students' proofs, we conclude that: there was a relation on the consistency and the students' levels of mathematically giftedness, being the least consistent the student not mathematically gifted and the most consistent the student with the highest level of mathematical giftedness; the variability was greater in the arithmetical problems; the quality of the proofs produced increased as the level of mathematical giftedness did; the two students with a lower level did better proofs in the arithmetical than in the geometrical problems, while the student with the highest level did not show significant differences between the two areas.

Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this scoping review, we provide a comprehensive overview of related research on proposed VLA methods, as well as identifying any gaps in the literature that could assist in describing new and helpful directions to the field. This review searched all relevant articles in five accessible databases -- Scopus, Web of Science, ERIC, ACM, and IEEE Xplore -- using 40 keywords. These studies were mapped, categorized, and summarized based on their objectives, the collected data, the intervention approaches employed, and the results obtained. The results determined what affordances the VLA tools allowed, what kind of visualizations were used to inform teachers and students, and, more importantly, positive evidence of educational interventions. We conclude that there are moderate-to-clear learning improvements within the limit of the studies' interventions to support the use of VLA tools. More systematic research is needed to determine whether any learning gains are translated into long-term improvements.

Learning analytics (LA) adoption is a challenging task for higher education institutions (HEIs) since it involves different aspects of the academic environment, such as information technology infrastructure, human resource management, ethics, and pedagogical issues. Therefore, it is necessary to provide institutions with supporting instruments to deal with these challenges. Although there has been much research on factors that are associated with the adoption of LA in HEIs, there has been much less research on specific models that can be used to guide actual adoption. In this sense, we developed MMALA, a Maturity Model for Adopting Learning Analytics. It is a guide that describes the necessary practices for taking the first steps in this area and enables institutions to reach higher levels of maturity in LA use, culminating in an organized and systematic adoption. In this paper, we describe the development process of MMALA, focusing on the model evaluation, which used both the questionnaire and the expert opinion method. MMALA can also give institutions an overview of their current situation regarding LA adoption. In this sense, we present the results of the maturity evaluation of three Brazilian HEIs using MMALA.

This mixed-methods study aims to investigate the bias in peer feedback. Thirty-two English as an additional language learners gave each other anonymous feedback on their texts. Half of the participants received feedback from their teacher disguised as peer feedback, while the other half received actual peer feedback. Data were collected through drafts of two essays, feedback, and a questionnaire. Results indicate that although participants reported trusting teacher feedback more, the quantitative uptake of feedback was similar regardless of the source. Data analysis suggests that the teacher's and peers' social representation plays a more significant role in uptake than the feedback itself.

Field-based practicum experiences are essential in connecting classroom theory to the real world. In this mixed methods study, we analyzed principal candidates' perceptions of their summer residency practicum experiences via a self-assessment principal leadership competency instrument and virtual semi-structured interviews. We found that principal candidates expressed leadership growth in the following Texas principal leadership competency areas: Strategic Operations, Human Capital, and Executive Leadership. These findings were consistent in our quantitative and qualitative data analysis. Conversely, the principal candidates stated that their greatest leadership challenges during the summer residency practicum involved providing instructional feedback and engaging in difficult conversations. The results of this study may assist principal preparation programs in revamping their curriculum to include a more meaningful residency-practicum experience.

A laboratory experiment was developed for the continuous flow preparation of an aminal derived from the condensation of furfural with morpholine. The experiment introduces the students to concepts of green chemistry, heterogeneous catalysis, and continuous flow. A cheap and easy setup allows the heterogeneous catalyst reactor to be built in class. The use of furfural reinforces the importance of green chemistry by using one of the key synthons obtained from biomass.

Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly challenging task as the number of students increases. Therefore, this article explores the use of automated content analysis to examine instructor feedback based on reputable models from the literature that provide best practices and classify feedback at different levels. For this, this article proposes using the transformer model BERT to classify feedback messages. The proposed method outperforms previous works by up to 35.71% in terms of Cohen's kappa. Finally, this study adopted an explainable artificial intelligence to provide insights into the most predictive features for each classifier analyzed.

This study assesses the acceptability, appropriateness, feasibility, and efficacy of a novel asynchronous video-based intervention for teaching respiratory physiology and anatomy to medical students in resource-limited settings. A series of short video lectures on pleural anatomy, pulmonary physiology, and pathophysiology was created using Lightboard and screen capture technology. These were uploaded to YouTube and Google Drive and made available to 1st-3rd year medical students at two Latin American universities for 1 week. Employing a parallel-convergent mixed methods design, we conducted surveys, focus groups, interviews, and pre/post testing for qualitative and quantitative data. Thematic Analysis was used to analyze qualitative data and McNemar's test for quantitative analysis. Seventy-six students participated. The videos' short format, interactivity, and Lightboard style were highly valued for their flexibility, time efficiency, and educational impact. Students recognized their clinical relevance and trusted their content, suggesting potential applicability in similar settings. Despite infrastructure and connectivity challenges, the use of flexible streaming and downloadable options facilitated learning. Survey results indicated high levels of feasibility (99%), appropriateness (95%), and acceptability (95%), with significant knowledge gains observed (37% correct pre-test answers vs. 56% post-test, p < 0.0001). Our findings demonstrate high acceptability, appropriateness, feasibility, and efficacy of a targeted asynchronous education centered on short-format videos in resource-limited settings, enabling robust learning despite local barriers. Flexible access is key for overcoming localized barriers. Taking an adaptive, learner-centered approach to content creation and delivery to address constraints was pivotal to success. Our modular videos could serve as versatile models for flexible education in resource-constrained settings.

The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find solutions stemming from the former, with the latter being less active. From the mathematical programming framework, this paper suggests a new direction for tackling this problem. For the first time in the literature, a procedure based on linear programming is proposed to attain estimates of local contingency tables. Based on this and the homogeneity hypothesis, we suggest two new ecological inference algorithms. These two new algorithms represent an important step forward in the ecological inference mathematical programming literature. In addition to generating estimates for local ecological inference contingency tables and amending the tendency to produce extreme transfer probability estimates previously observed in other mathematical programming procedures, these two new algorithms prove to be quite competitive and more accurate than the current linear programming baseline algorithm. Their accuracy is assessed using a unique dataset with almost 500 elections, where the real transfer matrices are known, and their sensitivity to assumptions and limitations are gauged through an extensive simulation study. The new algorithms place the linear programming approach once again in a prominent position in the ecological inference toolkit. Interested readers can use these new algorithms easily with the aid of the R package lphom.

Sensory Over-Responsivity (SOR) is an increasingly recognized challenge among children with neurodevelopmental concerns (NDC). To investigate, we characterized the incidence of auditory and tactile over-responsivity (AOR, TOR) among 82 children with NDC. We found that 70% of caregivers reported concern for their child's sensory reactions. Direct assessment further revealed that 54% of the NDC population expressed AOR, TOR, or both -- which persisted regardless of autism spectrum disorder (ASD) diagnosis. These findings support the high prevalence of SOR as well as its lack of specificity to ASD. Additionally, AOR is revealed to be over twice as prevalent as TOR. These conclusions present several avenues for further exploration, including deeper analysis of the neural mechanisms and genetic contributors to sensory processing challenges.

This study presents a learning-oriented assessment experience and examines the impact of communication and relationships on student satisfaction and on the acceptance of self- and peer-assessment. To this end, an analysis was conducted based on the data collected from engineering students in a subject with a high degree of creativity. The answers of online surveys (n = 180) were examined by using the structural equation modelling technique (SEM). The results indicate that effective, frequent, and timely communication and quality relationships play an important role in ensuring that formative assessment, based on teamwork, feedback and self- and peer-assessment, is perceived as easy to implement and useful for learning and skills development, which also increases student satisfaction. In addition, these perceptions have an important impact on students' acceptance of self- and peer-assessment, although students show more confidence in the teacher's judgement and concern about the validity and reliability of their peers' marks.

Background: Delivering effective feedback to large groups of students represents a challenge for the academic staff at universities. Research suggests that undergraduate students often ignore the Elaborated Feedback (EF) received via digital learning environments. This may be because instructors provide feedback in written format instead of using more engaging channels (e.g., audiovisual). Objectives: This quasi-experimental study examines the extent to which feedback format (video vs. written) influences students' perceptions of feedback, their decision to access EF messages related to high-stakes assignments in digital environments, and its impact on academic performance, while considering the effect of their academic engagement. Methods: A total of 171 undergraduate students received generic EF messages through a learning platform the day after submitting each course assignment. 78 students received EF in written format and 93 in video format. Results and Conclusions: Our results showed that feedback format influenced students' decision to access EF and their academic performance, but not their feedback perceptions. Students in the written-feedback group accessed EF messages more often, but students who received video-feedback performed better than their counterparts in the written-feedback group. Moderation analysis showed that the relationship between the feedback format and students' academic performance was moderated by their academic engagement, suggesting that students with lower levels of academic engagement may benefit from video-feedback. Takeaways: The results reveal that using video feedback in digital environments may influence students' decisions to process EF and their academic achievement, especially when it comes to students with lower levels of academic engagement.

Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with positive empirical results on computer programming formative activities and showing under what conditions gamification is effective still need to be included. Objectives: This study aimed to quantify the effects of gamification techniques in software tools that support computer programming learning applied to data-structures university students. The study focused on determining whether there are differences in learning when using gamification techniques in online exercising formative activities. The effects of gamification on learning objectives with diverse complexity are studied. Methods: The study was conducted on computer engineering university students following a pretest-intervention-posttest design. They were divided into control and experimental groups, where both used a bank of exercises in Moodle to support learning. The experimental group considered gamification techniques, including points, leaderboards, and badges. Results and Conclusions: Gamification techniques significantly outperformed in learning gains in exercising activities without gamification. Regarding learning complexity, increasing taxonomic complexity did not negatively affect gamification learning effects.

Introduction Long COVID is a multisystemic condition following acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) characterized by symptoms like fatigue, shortness of breath, cognitive dysfunction, pain, digestive [...]