Classification of Students by Success Predictors in the SPOC Programming Course

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15410%2F19%3A73596002" target="_blank" >RIV/61989592:15410/19:73596002 - isvavai.cz</a>

Výsledek na webu

<a href="https://obd.upol.cz/id_publ/333175888" target="_blank" >https://obd.upol.cz/id_publ/333175888</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21125/iceri.2019.1143" target="_blank" >10.21125/iceri.2019.1143</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Students by Success Predictors in the SPOC Programming Course

Popis výsledku v původním jazyce

Small private online courses (SPOC) are modern ways of online study methods based on small groups of students with the same or very similar specific study orientation. The present paper describes the partial results of a research study performed in the context of including the SPOC programming course in Basics of programming course designed for university training of future teachers of information science subjects in elementary and secondary schools in academic year 2018-2019. The aim of the research was to determine which groups of students can be identified by success predictors in the SPOC course with an emphasis on the basics of programming. The design of the research included quantitative data collection and assessment methods. The data collection was performed by means of a questionnaire of the authors’ own design with a total of 110 scale items (predictors), where the respondents indicated predictor significance on a scale (1 completely insignificant – 7 significant). Moreover, the Eysenck Personality Questionnaire (EPQ) and VARK Questionnaire ver. 7.8. were used. The questionnaire items focused on the following areas: student characteristics, teacher characteristics, educational environment characteristics, technological areas. A total of 13 respondents completed the whole survey but regarding the range of questionnaire items, the relevance of the study matches a quantitative analysis. The number of respondents fully corresponds with the possibilities of a research analysis of a SPOC course. These types of courses usually have a low number of students. The present research had the maximum possible number of students in the current study programme. The data were analysed by means of multidimensional statistical methods, primarily by means of cluster analysis methods, which provide graphical group models, but also a valid verification of group existence. The orientation model of possible groups of students was developed by means of a hierarchical cluster analysis. The orientation model was verified by means of the globalized cluster analysis K-means and ANOVA analysis of variance. The results suggest two groups of students based on predictors. Significant differences between the two groups are suggested by 26.5 % of predictors of the total number of 110. Based on the research findings and limitations, the results should not be generalized to include all SPOC courses with different specializations. The results are characteristic for a specific group of students with a specific study orientation at Palacký University Olomouc.

Název v anglickém jazyce

Classification of Students by Success Predictors in the SPOC Programming Course

Popis výsledku anglicky

Small private online courses (SPOC) are modern ways of online study methods based on small groups of students with the same or very similar specific study orientation. The present paper describes the partial results of a research study performed in the context of including the SPOC programming course in Basics of programming course designed for university training of future teachers of information science subjects in elementary and secondary schools in academic year 2018-2019. The aim of the research was to determine which groups of students can be identified by success predictors in the SPOC course with an emphasis on the basics of programming. The design of the research included quantitative data collection and assessment methods. The data collection was performed by means of a questionnaire of the authors’ own design with a total of 110 scale items (predictors), where the respondents indicated predictor significance on a scale (1 completely insignificant – 7 significant). Moreover, the Eysenck Personality Questionnaire (EPQ) and VARK Questionnaire ver. 7.8. were used. The questionnaire items focused on the following areas: student characteristics, teacher characteristics, educational environment characteristics, technological areas. A total of 13 respondents completed the whole survey but regarding the range of questionnaire items, the relevance of the study matches a quantitative analysis. The number of respondents fully corresponds with the possibilities of a research analysis of a SPOC course. These types of courses usually have a low number of students. The present research had the maximum possible number of students in the current study programme. The data were analysed by means of multidimensional statistical methods, primarily by means of cluster analysis methods, which provide graphical group models, but also a valid verification of group existence. The orientation model of possible groups of students was developed by means of a hierarchical cluster analysis. The orientation model was verified by means of the globalized cluster analysis K-means and ANOVA analysis of variance. The results suggest two groups of students based on predictors. Significant differences between the two groups are suggested by 26.5 % of predictors of the total number of 110. Based on the research findings and limitations, the results should not be generalized to include all SPOC courses with different specializations. The results are characteristic for a specific group of students with a specific study orientation at Palacký University Olomouc.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50301 - Education, general; including training, pedagogy, didactics [and education systems]

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ICERI2019 Proceedings

ISBN

978-84-09-14755-7

ISSN

2340-1095

e-ISSN

—

Počet stran výsledku

9

Strana od-do

4617-4625

Název nakladatele

International Association of Technology, Education and Development (IATED)

Místo vydání

Madrid

Místo konání akce

Seville

Datum konání akce

11. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—