Student profiles and factors affecting performance

Chansarkar, Bal; Michaeloudis, A.

doi:10.1080/00207390120974

Cited by 21 publications

(6 citation statements)

References 4 publications

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“…While a literature search using 'student profiling' or 'student profiles' as key phrases does produce numerous articles (Chansarkar & Michaeloudis, 2001;Darcan & Badur, 2012;Stes & Van Petegem, 2014;Tempelaar et al, 2018), few such studies are concerned about pre-module/course profiling of students' preferred learning styles (Cekiso, 2011;Kwembeya & Mbukusa, 2019). It is against this background that we profiled students in a 3rd Year Biotechnology course at the University of Namibia prior to the commencement of teaching and learning with the aim to understand the students' preferred learning styles.…”

Section: In Defense Of Student Profilingmentioning

confidence: 99%

Student Profiling as a Tool for Inclusive Instructional Design: A Case of a 3rd Year Biotechnology Class, University of Namibia

Sibanda¹,

Mbukusa²,

Kwembeya³

2021

FET

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Massification of Higher Education (HE) has made it difficult for teachers to design instructional strategies that are responsive to the diverse student needs. We here argue that student profiling is a handy tool that the HE teacher can use for inclusive instructional design by thoughtfully selecting learning and teaching strategies, and materials and supports that will maximise student achievement. We designed a student-profiling instrument focusing on capturing students’ biographical information, learning preferences, anticipated learning outcomes, personality traits, and learning related skills-set and administered to students in a 3rd Year Biotechnology class at the University of Namibia. The data on learning style preferences was analysed using the VARK Questionnaire (version 8.01) while a Chi-square (?2) test of association (SPSS software version 24) was used to determine whether there was a relationship between students’ preferred learning styles and the other variables. Seventy-five percent (75%) of the students had multimodal learning preferences while 25% were unimodal for kinesthetic learning style. No students preferred visual or auditory learning alone. The ?2 test revealed no significant relationship between students’ preferred learning styles and any of the other variables including age, place of origin, home language, home setting, residence during school semester, pre-course anticipation, skills set, and personality traits (P > 0.05). We conclude that profiling students’ learning preferences prior to teaching and learning helps HE teachers to tailor their instructional strategies to students’ learning style preferences, maximises epistemological access, as well as enhance inclusivity, equality and equity.

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Section: In Defense Of Student Profilingmentioning

confidence: 99%

Student Profiling as a Tool for Inclusive Instructional Design: A Case of a 3rd Year Biotechnology Class, University of Namibia

Sibanda¹,

Mbukusa²,

Kwembeya³

2021

FET

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“…Academic performance means the ability of students to study and learn certain subjects in the school whether at the primary, secondary or tertiary institution levels with the aim of performing excellently in the course of study (Baxter & Haff, 2000). It could be described as notable actions or achievements by certain students in their field of study or discipline (Danesy, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…It could be described as notable actions or achievements by certain students in their field of study or discipline (Danesy, 2004). Academic performance is measured through achievement test which is also known as paper and pencil test (Baxter & Haff, 2000). Achievement test is a type of ability test designed to measure what an individual had learnt at the end of a course of instruction.…”

Section: Introductionmentioning

confidence: 99%

Influence of Social Status on Academic Performance of Secondary School Students with Disabilities in Kwara State

Famolu¹

2023

CJFY

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This study investigated the influence of social status on academic performance of secondary school students with disabilities in Kwara state. The descriptive survey of a correlational type was adopted for this study. The population for the study comprised all secondary school students with disabilities in Kwara State, while 200 students with disabilities constituted a sample for the study. Social Peer Rejection Scale developed by Asher et al.’s (2001) was adapted for this study. The adapted scale was validated and has a reliability coefficient of 0.89. The data collected were analysed using percentage for demographic data and research questions while the two null hypotheses formulated were tested at 0.05 level of significance using Pearson’s Product Moment Correlation (PPMC). The results of the findings revealed that 87.0% (n=147) of the secondary school students with disabilities were social rejected and as a result, it has negative influence of the academic performance. The findings also showed that social acceptance influences academic performance of students with disabilities in Kwara State. Implications for counselling practice and recommendations were also made.

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“…So that it is said that possibility of research is always there to find out what are the factors that affect the performance of the students. 3…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study to Assess the Academic Performance and Factors Affecting it among Higher Secondary School Students in Both Rural and Urban Areas of Vadodara.

2020

IJPHRD

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Background of the Study: The student's academic performance is plays a important role in producing the good quantity alumnae who will become manpower and leader of a particular country, and it is consequently responsible for country's economic and social development. Economical, personal, psychological, and environmental factors affect the Student's performance. Aims and Objectives:The aim of the study was to compare the academic performance and factors affecting it among higher secondary school students in both rural and urban areas of Vadodara. Material and Method:Comparative research design, and a non-probability convenience sampling technique was adopted to achieve the goal of the study. The tool consists of two parts. First part consists demographic data of the sample and second part consists of self-modified academic appraisal scale. The sample was 200 students those were taken from selected higher secondary schools of urban and rural areas of Vadodara. Results:The collected data was tabulated and analyzed using comparative and inferential statistics. In urban higher secondary school student's mean percentage was 73.78 and urban student's mean percentage was 66.47, and difference between it was 7.38%. Conclusion:According to the calculation of mean score of academic performance indicates that there was higher academic performance among higher secondary school students of urban area compare with rural area.

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Student profiles and factors affecting performance

Cited by 21 publications

References 4 publications

Student Profiling as a Tool for Inclusive Instructional Design: A Case of a 3rd Year Biotechnology Class, University of Namibia

Student Profiling as a Tool for Inclusive Instructional Design: A Case of a 3rd Year Biotechnology Class, University of Namibia

Influence of Social Status on Academic Performance of Secondary School Students with Disabilities in Kwara State

A Comparative Study to Assess the Academic Performance and Factors Affecting it among Higher Secondary School Students in Both Rural and Urban Areas of Vadodara.

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