Automated Assessment and Microlearning Units as Predictors of At-Risk Students and Students’ Outcomes in the Introductory Programming Courses

Jan Skalka,Martin Drlik

doi:10.3390/app10134566

Abstract

The number of students who decided to study information technology related study programs is continually increasing. Introductory programming courses represent the most crucial milestone in information technology education and often reflect students’ ability to think abstractly and systematically, solve problems, and design their solutions. Even though many students who attend universities have already completed some introductory courses of programming, there is still a large group of students with limited programming skills. This drawback often increases during the first term, and it is often the main reason why students leave study too early. There is a myriad of technologies and tools which can be involved in the programming course to increase students’ chances of mastering programming. The introductory programming courses used in this study has been gradually extended over the four academic years with the automated source code assessment of students’ programming assignments followed by the implementation of a set of suitably designed microlearning units. The final four datasets were analysed to confirm the suitability of automated assessment and microlearning units as predictors of at-risk students and students’ outcomes in the introductory programming courses. The research results proved the significant contribution of automated code assessment in students’ learning outcomes in the elementary topics of learning programming. Simultaneously, it proved a moderate to strong dependence between the students’ activity and achievement in the activities and final students’ outcomes.

Highlights

The current demand for experts in information technology (IT) as well as the prognosis of the future development on the labour market cause the constant growth of computer science education popularity, and a continual demand for improving the IT skills of the large group of graduates who enter the labour market every year.The number of students who decided to study IT-related study programs is continually increasing.Higher educational institutions which train the future IT professionals in different study programs react to this situation differently
Many universities admit as many students to study IT-oriented study programs as their capacities allow, besides considering their current ranking and the position in the country or worldwide
The list of admitted students with the number of points awarded in the admission process used primarily in pretest; the test results of students in two tests realised after introductory course part and object-oriented course part used for evaluation of used objects and method; learning management systems (LMSs) Moodle log used for the assessment of the activities of the students and dependency identification; the parts of the log were processed to use for relevant calculation

Summary

Introduction

The current demand for experts in information technology (IT) as well as the prognosis of the future development on the labour market cause the constant growth of computer science education popularity, and a continual demand for improving the IT skills of the large group of graduates who enter the labour market every year.The number of students who decided to study IT-related study programs is continually increasing.Higher educational institutions which train the future IT professionals in different study programs react to this situation differently. Many universities admit as many students to study IT-oriented study programs as their capacities allow, besides considering their current ranking and the position in the country or worldwide. They often expect that this number of students will naturally decrease during the first months of the term. Even though this process can be considered natural, it opens the discussion, how to teach this large group of newcomers with a different introductory level of IT skills effectively and how to set up the safety net for the at-risk students with higher predisposition to leave a study too early

Methods

Results

Conclusion