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The main purpose of this study was to explore the impact of the Tigray People Liberation Front (TPLF) armed violence on educational institutions, students' educational attainments, and the role of actors playing in school governance and redirecting the education process. This study was positioned to yield preliminary evidence which can serve as input for concerned bodies when designing intervention programs in the study area that aims to give a response to the spoiled education system brought by the violence. In doing so, a convergent mixed-method research design was used. The study sample was bounded to n = 398 participants. Both qualitative and quantitative data were collected simultaneously, and the analysis was drawn upon both strands in search of patterns. As a result, the following findings were obtained. The TPLF armed violence instigated the destruction of school infrastructures and generated substantial impediments to the supply of schooling. As a result, students' educational attainment and learning outcomes were significantly lowered as compared to before the violence. As well, students' dropout rate, out-of-school students' rate, and related educational wastage have been amplified. This, in turn, requires sound school governance and the active participation of all actors including parents and the local community at large be part of the solutions for those educational issues hampered by the TPLF violence. In the end, possible conclusions and suggestions were made.

Gamification research in educational settings has produced mixed results on student learning outcomes. Educational researchers and practitioners both struggle with identifying when, where, and how to use gamification design concepts. The present study provides findings from a meta-analysis that integrated the empirical, quantitative research on gamification in formal educational settings on student learning outcomes. This was achieved by examining the overall effect size, identifying which gamification design elements (e.g., badges) were used, and determining under what circumstances (e.g., engineering education) gamification works. The final corpus of data included 30 independent studies and associated effect sizes comparing gamification to non-gamification conditions while accounting for N  = 3083 participants. The overall effect size using a random-effects model is g  = .464 [.244 to .684] in favor of the gamification condition, which is a small to medium effect size. We examined 14 different gamification design elements (e.g., leaderboards) and showed that each leads to different effects on student learning outcomes. Further, the type of publication (e.g., journal article), student classification (e.g., undergraduate), and subject area (e.g., mathematics) are also investigated as moderators. We provide a discussion of our findings, some recommendations for future research, and some brief closing remarks.

The prediction of student academic performance has drawn considerable attention in education. However, although the learning outcomes are believed to improve learning and teaching, prognosticating the attainment of student outcomes remains underexplored. A decade of research work conducted between 2010 and November 2020 was surveyed to present a fundamental understanding of the intelligent techniques used for the prediction of student performance, where academic success is strictly measured using student learning outcomes. The electronic bibliographic databases searched include ACM, IEEE Xplore, Google Scholar, Science Direct, Scopus, Springer, and Web of Science. Eventually, we synthesized and analyzed a total of 62 relevant papers with a focus on three perspectives, (1) the forms in which the learning outcomes are predicted, (2) the predictive analytics models developed to forecast student learning, and (3) the dominant factors impacting student outcomes. The best practices for conducting systematic literature reviews, e.g., PICO and PRISMA, were applied to synthesize and report the main results. The attainment of learning outcomes was measured mainly as performance class standings (i.e., ranks) and achievement scores (i.e., grades). Regression and supervised machine learning models were frequently employed to classify student performance. Finally, student online learning activities, term assessment grades, and student academic emotions were the most evident predictors of learning outcomes. We conclude the survey by highlighting some major research challenges and suggesting a summary of significant recommendations to motivate future works in this field.

Using survey data from 156 bachelor's-granting institutions, this study explored the relationship between academic advising services and seniors' grades and self-perceived gains. We found advising experiences has a positive relationship with students' grades and self-perceived gains. In addition, our results indicate that the institutional advising climate is positively correlated with perceived gains, but not grades. The results also showed that the relationships between advising and students' learning and development varied across institutions. Implications for policy and practice were discussed.

Undergraduate programs that focus on disciplinary knowledge and skills can reinforce pre-existing mindsets or ideologies that can lead to insufficient questioning of certain types of information (e.g., empirical data or model results) or insufficient valuing of certain types of information (e.g., Indigenous knowledge).  One way to address this challenge is to include values-based learning and assessment strategies that empower students to better understand and engage with their complex and changing worlds.  General Education (GenEd) Capstone Experiences (CE) often seek to instill such values, but scholarly analysis of the pedagogies and their effectiveness is limited, as is discussion on the inclusion of similar pedagogies in discipline-focused courses. This study addresses this research disparity by using a mixed methods approach to investigate student and faculty perceptions of the values integrated by a GenEd CE program and the pedagogies used to integrate those values.  Results demonstrate that the integration of reflection and discussion pedagogies has the potential to influence a variety of values-based outcomes, including thoughtfulness, openness, and responsibility.  Institutional leaders and CE instructors may integrate these pedagogies into their CEs, with mindful attention to the associated values that they seek to instill. 

Undergraduate programs that focus on disciplinary knowledge and skills can reinforce pre-existing mindsets or ideologies that can lead to insufficient questioning of certain types of information (e.g., empirical data or model results) or insufficient valuing of certain types of information (e.g., Indigenous knowledge).  One way to address this challenge is to include values-based learning and assessment strategies that empower students to better understand and engage with their complex and changing worlds.  General Education (GenEd) Capstone Experiences (CE) often seek to instill such values, but scholarly analysis of the pedagogies and their effectiveness is limited, as is discussion on the inclusion of similar pedagogies in discipline-focused courses. This study addresses this research disparity by using a mixed methods approach to investigate student and faculty perceptions of the values integrated by a GenEd CE program and the pedagogies used to integrate those values.  Results demonstrate that the integration of reflection and discussion pedagogies has the potential to influence a variety of values-based outcomes, including thoughtfulness, openness, and responsibility.  Institutional leaders and CE instructors may integrate these pedagogies into their CEs, with mindful attention to the associated values that they seek to instill. 

Higher education is essential because it exposes students to a variety of areas. The academic performance of IT students is crucial and might fail if it isn’t documented to identify the features influencing them, as well as their strengths and shortcomings. The student academic prediction system needs to be enhanced so that teachers can forecast their students’ performance. Numerous studies have been conducted to increase the prediction accuracy of IT students, but they encountered difficulties with unbalanced data and algorithm tuning. To address these issues, the study proposed different machine learning (ML) algorithms that handled imbalanced data by applying the synthetic minority oversampling technique (SMOTE) and employing hyperparameter tuning algorithms to enhance prediction during the training process. The ML models we used were decision tree (DT), k-nearest neighbor, and XGBoost. The models were fine-tuned by applying Ant colony optimization (ACO) and artificial bee colony optimization techniques. Subsequently, these optimization techniques further enhanced the performance of the models. After comparing them, the results showed that SMOTE and ACO combined with the DT model outperformed other models for academic prediction. Additionally, the study utilized the Kendall Tau correlation coefficient technique to analyze the correlation between features and identify factors that positively or negatively impact student success.

The emerging Flipped Classroom approach has been widely used to enhance teaching practices in many subject domains and educational levels, reporting promising results for enhancing student learning experiences. However, despite this encouraging body of research, the subject domain of Information and Communication Technologies (ICT) teaching at K-12 education has not yet been explicitly researched. This is a considerable shortcoming given (a) the globally acknowledged need to effectively design and deliver ICT curricula to students at all levels of school education (primary, junior and senior secondary) towards cultivation of digital competences, and (b) the recurring research evidence that the Flipped Classroom approach can enhance students' learning experiences in Science, Technology, Engineering and Math (STEM) K-12 education. Therefore, the contribution of this paper is the design and implementation of an action research for studying the effect of the Flipped Classroom approach in K-12 ICT teaching and learning. The action research employed a quasi-experimental design using experimental-control groups, from two classes (a total of 46 students) for an entire semester of the school year following the National (Greek) Curriculum in junior high school ICT studies. The results of this study provide evidence for potential advantages in students' cognitive learning outcomes related to subject domain knowledge, the exploitation of teaching time during the classroom face-to-face sessions, the students' level of motivation, as well as their level of engagement.

Technology enhancement learning is a process that leads to deep point of learning and adds knowledge of technologies. Various studies shed light on technology development and its effect in educational sector. The aim of this integrative review is to examine the current evidence of the impact of technology learning on student learning and academic performance in courses requiring collaborative or activities. The authors searched electronic databases for relevant articles, with different learning techniques. 24 articles met the requirement of paper, it’s collected from (2011-2017). Three themes of techniques used for student learning outcomes, includes technology enhanced learning, assessment method and faculty experience on academic performance in universities with technology use. The final results of this paper show the relationship between what has been done and the factors used by the authors. Also the future work needs more use of technologies in different phases of learning process.

Faculty and assessment professionals rely on Bloom’s taxonomy to guide them when they write measurable student learning outcomes and describe their goals for developing students’ thinking skills. Over the past ten years, assessment offices and teaching and learning centers have compiled lists of measurable verbs aligned with the six categories that comprise Bloom’s taxonomy. The author analyzed 30 compilations posted on web sites and evaluated how well these verbs aligned with categories in Bloom’s taxonomy. The author discusses the value of Bloom’s taxonomy as a heuristic for writing student learning outcomes and other factors faculty should consider when they articulate learning outcomes to describe levels of expertise attained by students who complete an associate’s, bachelor’s, or graduate degree.