Estimating the Academic Performance of Secondary Education Mathematics Students: A Gain Lift Predictive Model

Influence of motivation on the perception of mathematics by secondary school students

Motivation, the teacher-student relationship, the use of resources, and the time spent studying, in addition to the family economic and social context, are some of the factors that affect academic performance and directly influence student failure. This paper evaluates the motivation in mathematics students' performances by analyzing indicators of the mathematics learning dimensions. A total of 2,018 secondary students were evaluated in this cross-sectional study. Motivation, teaching, resources, and study time were analyzed with a validated 20-item questionnaire. Statistical analysis revealed that student motivation appears to be significantly related to perceptions of teaching practices and the use of resources for study. Students with high motivation have positive perceptions of teaching practices. Gender differences were not observed. In addition, the motivation indicator allowed for grouping students into various motivational profiles.

COVID-19 Emergency Remote Teaching Opinions and Academic Performance of Undergraduate Students: Analysis of 4 Students’ Profiles. A Case Study

Distance learning due to the COVID-19 lockdown, commonly called emergency remote teaching (ERT), substantially changed the methodology of teaching and possibly students’ perceptions of the quality of lectures. Students’ opinions should be collected and analyzed jointly with other data such as academic performance to assess the effect of this pandemic on learning. A 20-question, 4-point Likert scale specific questionnaire was designed and validated twice by a panel of experts. The survey was sent to the 365 industrial engineering undergraduate students enrolled in a chemistry course. Responses (n = 233) and academic data were collected, and four student profiles were identified by using the k-means cluster analysis technique: ‘The Lucky’, ‘The Passive’, ‘The Autonomous Learner’ and ‘The Harmed’. Students experienced the ERT differently according to their profile. Undergraduates who were better autonomous learners excelled in academic performance and were more participative in the survey. In general, students preferred face-to-face classes over distance learning. Undergraduates’ learning has been impaired due to the circumstances. However, contrary to their beliefs, the situation has benefited them with respect to grades when comparing their performance with students from previous years. Discovering what challenges students faced to adapt to the situation is key to giving students tools to grow as autonomous learners and to enable educators to apply tailored teaching techniques to improve the quality of lectures and enhance student satisfaction.

Positioning–Emotions Association of Young Students Using Digital Technology

Researchers in social semiotics have shown students’ emotions to be associated with their positioning, an association which contributes to students’ cognitive processes and, therefore, to their learning. Nevertheless, this association between emotions and positioning, especially with regard to very young students, has not been extensively investigated with qualitative methods. The present work considers the positioning–emotions association in the context of third-grade students using digital technology to study relationships among quadrilaterals. The entire learning process of eight students, divided into four pairs, was recorded on video; the transcripts were then analyzed using qualitative and quantitative methods to understand the relationship between positioning and emotion constructs. A chi-square test was run for the transcribed data to find the correlations between constructs for positioning and emotions. We found a strong connection between outsiderness and boredom and between leadership confidence; moderate connections were found between outsiderness and powerless, help-seeking and confusion, and collaboration and interestedness. We used the discursive framework for connecting positioning with emotions to encode the data and triangulate our qualitative and quantitative findings. By these means, we were able to draw conclusions regarding the role of digital technology in determining students’ positioning and of the teacher in modifying undesirable positioning and its associated emotions.