Psychosocial and educational intervention approaches employ diverse treatment frameworks, most of which involve delivering some form of feedback to participants about their behavior. General conceptions of feedback are well-known to underlie mainstream therapeutic and educational approaches. Recently emerging ‘smart’ approaches also rely on feedback principles. However, little scholarship is available to stitch together evolving strands of feedback principles and no literature characterizes explicitly the diverse landscape of feedback practices employed in education or intervention science. This paper reviews intrinsic conceptions of feedback along with diverse cases of its use in intervention and education. Based on our consideration, we present a typology of feedback modalities that we hope will enrich the efforts of interventionists and educators to design treatment and educational frameworks incorporating feedback.

Higher education institutions have focused their efforts on promoting research seedbeds as a strategy for formative research. In this regard, the impact of such a strategy remains unknown due to the lack of models that enable its evaluation. Therefore, this study aimed to design an evaluation model for the academic productivity of research seedbeds based on the available evidence in the literature. To achieve this, a systematic review was conducted following the PRISMA model, analyzing 53 documents including articles, book chapters, and conference proceedings from the SCOPUS, ProQuest, Jstor, Scielo, and ScienceDirect databases. The results identified indicators that allowed for the design of a model based on six constructs: research training, institutional capabilities, bibliographic production, innovation and development, social appropriation of knowledge, and human resource training. It was concluded that the indicators evaluating research seedbeds seek greater scientific development involving students and improving the quality of research products, which directly impacts the institutional research mission.

School attendance problems are of great research interest, which is reflected in the increase of scientific publications. This increase hinders the adequate follow-up and updating of the scientific community on the subject. The aim of the present bibliometric study lies in the review of the scientific literature published on school attendance problems during 2014-2021. A bibliographic search and analysis of scientific articles was performed, obtaining a definitive sample of 700 documents. Results were extracted and analyzed for the following indicators: temporal productivity, productivity by authors, co-authorship index, productivity by journals, use of topics, research areas addressed and types of samples used. The number of publications indicates a progressive increase of interest on the subject, which has not corresponded to the creation of a specific journal on the subject. There is also evidence of the need for consensus on the topics to be used; the preference for knowing the factors associated with school attendance problems over other areas of research; and the generalized use of community samples as opposed to more specific ones. In conclusion, the characteristics researched on school attendance problems are presented; knowledge that will facilitate the establishment of intervention processes applicable to different contexts and realities.

The world eagerly anticipates advancements in AI technologies, with substantial ongoing research on the potential AI applications in the domain of education. The study aims to analyse publications about the possibilities of artificial intelligence (AI) within higher education, emphasising their bibliometric properties. The data was collected from the Scopus database, uncovering 775 publications on the subject of study from 2000 to 2022, using various keywords. Upon analysis, it was found that the frequency of publications in the study area has risen from 3 in 2000 to 314 in 2022. China and the United States emerged as the most influential countries regarding publications in this area. The findings revealed that “Education and Information Technologies” and the “International Journal of Emerging Technologies in Learning” were the most frequently published journals. “S. Slade” and “P. Prinsloo” received the most citations, making them highly effective researchers. The co-authorship network primarily comprised the United States, Saudi Arabia, the United Kingdom, and China. The emerging themes included machine learning, convolutional neural networks, curriculum, and higher education systems are co-occurred with AI. The continuous expansion of potential AI technologies in higher education calls for increased global collaboration based on shared democratic principles, reaping mutual advantages.

This research aimed to explore the influence of a robotic program using the robot kit "RoboBuilder RQ+110" on students' attitudes toward effective communication. The study used a quantitative research design and involved 475 grade 4 (10 years old) students from Malaysia's Selangor and Malacca states. A quasi-experimental research (pre-test & post-test) approach with control and experimental groups was adopted, and the data were analyzed with inferential statistical test and repeated measures analysis of variance (ANOVA) using SPSS 25 software at 0.05 significance level. Questionnaires were administered to collect data from the experimental and control groups. The results showed statistically significant changes (α ≤ .05) in attitudes toward effective communication for the experimental group that received a robotics program compared with the control group. The study results suggest that innovative technological tools or programs such as robotics programs are recommended as innovative science, technology, engineering, and mathematics (STEM) program rooted in constructivism to improve students' attitudes toward effective communication.

<p style="text-align:justify">Recently, a large-scale study of college students&rsquo; motivation orientations when they transitioned to online learning because of the global COVID-19 pandemic found that unlike prior studies, in the 3 x 2 goal orientation framework the standard for competence (self, other, task) was of greater importance than valence (approach, avoidant). Moreover, previous research found students&rsquo; different goal orientations related to how they responded to the shutdown academically from both volition and social perspectives. We investigated whether a three-factor model would replicate with unique undergraduate cross-cultural samples, and we wanted to examine how students with different goal orientations responded to the shutdown of their universities due to the pandemic. Students from a U.S. university and students from Oman completed a 44-item goal orientation survey, a demographic survey, and an 11-item survey to assess students&rsquo; experiences following the pandemic. Results indicate that students who set task-based goals were less likely to have negative experiences related to the social aspects of the pandemic and those students who had negative responses to the lack of social contact were also expected to have lower grades.</p>

This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.