Over the last few decades, computer programming has become an important field of endeavor due to rapid development in the information sector. Despite the importance of programming, there is a growing concern that it is relatively difficult. In the process, researchers have started employing media tools to reduce programming difficulties and motivate learners to approach programming problems. One of the common tools widely used is program animation—an instructional medium that incorporates animated characters. However, little is known about the research trends in this field of study. This article, therefore, employed a systematic mapping method to review this trend to find patterns and gaps left in the literature. The study extracted 48 articles published between 2000 and 2022 from four scientific databases (Web of Science, Scopus, ScienceDirect, and ERIC) and three digital libraries (ACM Digital Library, IEEE Xplore Digital Library, and Wiley Online Library). The review discovered important trends. First, there is a paucity of research evidence evaluating program animation in the context of secondary and elementary levels; the majority of the extracted studies focused on participants from tertiary institutions. A similar paucity of research evidence employing mixed methods and qualitative approaches was also noted. Scratch programs were used in recent research more often than other program animations. There is also too little evaluation of psychomotor variables. Finally, there exist inconsistent findings on the effect of program animation although plenty of studies revealed positive results in favor of these media tools. The study therefore recommends that future research should be conducted to fill these identified gaps.

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This paper outlines briefly, some views of the term “ Educational Technology” and its role generally in the field of education as evident from research findings. The urgent need for low-cost educational technology for schools and colleges in Nigeria is discussed. Attention is also drawn to the need to re-orient the teacher to his task, if new methods and media are to be used successfully. Finally, it is further suggested that future use of the achieved methods and media may differ radically depending among other things on the objectives to be achieved and the en­try behaviour of the students, particularly when we employ the low-cost educational technology for effective learning hnd teaching. The importance of an Educational Resource Centre, and Teachers’ Resource Centre are among other things strongly suggested.

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The study tracked and modeled public perceptions toward the reality of COVID-19 pandemic in Nigeria over a 3 month period (10 May to 10 August 2020); 2580 Nigerians across the six geopolitical zones were selected to participate in the study. These participants were selected from various social media platforms and were requested to complete an online survey over a 3-month period. Data were analyzed in three phases: tracking, modeling, and forecasting. We first tracked the respondents’ perceptions in the form of a qualitative response, where seven thematic constructs emerged from content analysis. These constructs were confirmed in the modeling phase, using structural equation modeling after data transformation. The themes were forecast as a single construct to predict possible trends and patterns over the next 3 month period using an autoregressive integrated moving average. Our findings revealed that public perceptions toward the reality of COVID-19 pandemic in Nigeria fall into seven thematic constructs: “scam,” “fake,” “politics,” “business venture,” “exaggeration,” “real,” and “real but manipulated.” These constructs show a steady trend with a random walk pattern, suggesting that perceptions toward the reality of COVID-19 in Nigeria will remain relatively unchanged over the next 3 month period. We recommend, among other things, that massive and intensive sensitization and awareness programs are needed to change the public mindset concerning the reality of the pandemic in Nigeria.

Studies examining students’ learningbehavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In this research, we confirm the possibilities of classifying students’ learning behavior using data obtained from multimodal distribution. We employed computer algorithms to classify students’ learning behavior in animated programming classrooms and used information from this classification to predict learning outcomes. Specifically, our study indicates the presence of three clusters of students in the domain of “stay active”, “stay passive”, and “to-passive”. We also found a relationship between these profiles and learning outcomes. We discussed our findings in accordance with the engagement and instructional quality models and believed that our statistical approach will support the ongoing refinement of the models in the context of behavioral profiling and classroom interaction. We recommend that further studies should identify different epistemological frames in diverse classroom settings to provide sufficient explanations of students’ learning processes.

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