Farm women need different types of farm information due to higher engagements in agriculture. It is observed from various studies that majority of the farm women were under low social participation and cosmopoliteness level. So, on the basis of the findings, a study was conducted to identify the farm women participation, association and cosmopoliteness with different organisations and to analysis their networking structure in a social system. The study was conducted in Cooch Behar district of West Bengal with the help of expost facto research design. It was found from the study that majority of the farm women were associated with one organisation and regularly involved in self-help groups. It was found from the study that the panchayat office, nearest town, kisan mandi, Krishi Vigyan Kendra, nearest city and the post office play important roles for networking the farm women.

Technology is relevant in achieving educational development. Exploring how best to pattern and incorporate educational technology to engender sustainability remains relevant. It is against this backdrop that this study examined the Prospect of online instructional delivery in sub-Saharan African Universities using Google Classrooms ascertained concerning usability and accessibility while examining impending challenges. This study adopted a descriptive survey design. The study population was undergraduates enrolled at the University of Ilorin, Nigeria, a public institution owned by the Federal Government of Nigeria and the most soughed institution in terms of admission in the country. The target population was teacher trainees exposed to online instructional using Google Classrooms for 2018/2019 academic session. The study participants were purposively sampled; a total of 1933 participants. Data were gathered using a researcher designed questionnaire which was face and content validated. Three research questions were stated to examine accessibility, usability and challenges while the tested hypotheses were concerning prospects of Google Classroom for University of Ilorin undergraduates' learning across gender and departmental divides. Both descriptive statistics (Research Questions) and inferential statistics (Hypothesis) were employed in analysing data collected gathered. Significant findings revealed that Google Classroom holds prospects for innovative instructional approach for university undergraduates’ learning. However, there is a need to improve its level of accessibility to undergraduates to maximise its gains by making efforts to alleviate the challenges militating against smooth access to ensure sustainability in higher education in sub-Saharan Africa, apt in the current pandemic era.

Teaching and learning have gone online in response to the pandemic, which reveals the need for accurately tailored educational assessments to ascertain the extent to which learning outcomes or objectives are achieved. Computer Adaptive Testing (CAT) is a technology-driven form of assessment that tailors items to a candidate's ability level with empirically proven benefits over the fixed-form computer based test. A systematic review was employed which shows that item bank is a key requirement for CAT and the items must through a rigorous item development process to ensure and maintain quality in terms of content, criterion constructs and internal consistency, determining the psychometric validation of behavioural measures while leveraging on variances of Item Response Theory (IRT). Following the item development stage is the need to compile validated items into administrable forms using advanced computer software for automatic test assembly and administration, such as FastTest which allows specifying empirically tried algorithms for CAT from start to termination of the test. This helps to ensure that assessment properly leverages the advantages that CAT holds. Furthermore, the review revealed that CAT has been widely applied with large-scale testing in various fields by educational, health and psychological professionals utilising different IRT models; however only in developed countries. This brings to bear the need for adoption in other parts of the world, for improvements in educational assessments. The interjections of 4IR with AI considering emerging technology aids the CAT algorithm for achieving expert and knowledge-based systems, being a requirement for survival in today’s world.

Challenges of a lack of formal technology-embeded teacher training, collaborative learning models, adequate technology know-how, and internet access are barriers to adopting technological-enabled teaching and learning STEM subjects in the African context. This study examined technology adoption for STEM in higher education while evaluating students’ experiences with evidence and implications for less developed countries. The survey research design was adopted for the study. The study population was students in higher learning institutions in selected countries in the sub-Saharan African region using a multi-stage sampling procedure consisting of convenience and purposive sampling techniques. A self-developed questionnaire titled Technology Adoption for Teaching and Learning Questionnaire “TATLQ” premised on the unified theory of acceptance and use of technology (UTAUT) model was used for data collection. The instrument had an overall reliability coefficient of 0.96. The collated data were analysed using descriptive of the median and a network chart to answer the research questions. In contrast, the inferential statistics of t-test and Analysis of Variance statistics were used to test the hypothesis generated for the study and implemented in the psych package of R programming language version 4.0.2 software. Findings revealed that students had a positive experience with online teaching and learning and concluded that technology adoption for STEM education online teaching and learning is feasible in sub-Sahara Africa, with the need for improvements in internet access and technical support on the basis for which recommendations were made.

<p><span lang="EN-US">Computer adaptive testing (CAT) is a technological advancement for educational assessments that requires thorough feasibility studies through computer simulations to ensure strong testing foundations. This advancement is especially germane in Africa being adopters of technology, and this should not be done blindly without empirical evidence. A quasi-experimental design was adopted for this study to establish methodological choices for CAT ability estimation. Five thousand candidates were simulated with 100 items simulate through the three-parameter logistic model. The simulation design stipulated a fixed-length test of 30 items, while examinee characteristics were drawn from a normal distribution with a mean of 0 and a standard deviation of 1. Also, controls for the simulation were set not to control item exposure or to use the progressive restricted method. Data gathered were analyzed using descriptive statistics (mean and standard deviation) and inferential statistics (Two-way multivariate analysis of variance: MANOVA) for testing the generated hypotheses. This study provided empirical evidence for choosing ability estimation methods for CAT as part of the efforts geared towards designing accurate testing programs for use in higher education.</span></p>