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Abstract-Student performance modelling (SPM) is a critical step to assessing and improving students' performances in their learning discourse. However, most existing SPM are based on statistical approaches, which on one hand are based on probability, depicting that results are based on estimation; and on the other hand, actual influences of hidden factors that are peculiar to students, lecturers, learning environment and the family, together with their overall effect on student performance have not been exhaustively investigated. In this paper, Student Performance Models (SPM) for improving students' performance in programming courses were developed using M5P Decision Tree (MDT) and Linear Regression Classifier (LRC). The data used was gathered using a structured questionnaire from 295 students in 200 and 300 levels of study who offered Web programming, C or JAVA at Federal University, Oye-Ekiti, Nigeria between 2012 and 2016. Hidden factors that are significant to students' performance in programming were identified. The relevant data gathered, normalized, coded and prepared as variable and factor datasets, and fed into the MDT algorithm and LRC to develop the predictive models. The developed models were obtained, validated and afterwards implemented in an Android 1.0.1 Studio environment. Extended Markup Language (XML) and Java were used for the design of the Graphical User Interface (GUI) and the logical implementation of the developed models as a mobile calculator, respectively. However, Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE) and the Root Relative Squared Error (RRSE) were the metrics used to evaluate the robustness of MDT and LRC models. The evaluation results obtained indicate that the variable-based LRC produced the best model in terms of MAE, RMSE, RAE and the RRSE having yielded the least values in all the evaluations conducted. Further results obtained established the strong significance of attitude of students and lecturers, fearful perception of students, erratic power supply, university facilities, student health and students' attendance to the performance of students in programming courses. The variable-based LRC model presented in this paper could provide baseline information about students' performance thereby offering better decision making towards improving teaching/learning outcomes in programming courses.

Difficulties inherent in human face recognition from unconstrained and motion characterized scenes are usually accounted for due to varying illumination and pose of subjects in the scenes. However, a number of technical approaches have been developed to manage these nuisance factors to make recognition possible and optimal. In this paper, a review of some technical approaches to face recognition challenged with varying illumination and pose is conducted. The logical soundness of each approach and limitations are investigated while a basis for a unified, more efficient and technically optimal approach is established.

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This study focuses on fostering students' cognitive achievement using students-concept maps and demonstration in chemistry. A pre-test, post-test control groups 3 x 3 x 2 factorial design was employed. A total of two hundred and forty eight senior secondary two students drawn from three public secondary schools in Ogun state of Nigeria participated in the study. Stratified random sampling technique was used in drawing the schools. Intact classes of students were used for the study. Three research questions and three hypotheses guided the study. Treatment that lasted for four weeks involved teaching redox reaction concepts to experimental groups using students-directed concept mapping, demonstration while the control group was taught using lecture method. Test of Knowledge in Redox Reaction (TKRR) was the instrument for data collection. Mean and standard deviation were used to answer the research questions while the hypotheses were tested with Analysis of covariance (ANCOVA). Results revealed that there was significant difference in the cognitive achievement of students taught using students-directed concept mapping, demonstration and lecture method. Experimental groups' achievement was significantly better than those taught using lecture method. Also ability level is significant factor on students' cognitive achievement in Redox reaction. However, no significant difference was found on the effect of gender on cognitive achievement. Based on the findings, the use of students-directed concept mapping and demonstration strategies to foster cognitive achievement in difficult concept like Redox reaction in chemistry was recommended to chemistry teachers.