Evaluating the effectiveness of educational data mining techniques for early prediction of students' academic failure in introductory programming courses

2017 ◽  
Vol 73 ◽  
pp. 247-256 ◽  
Author(s):  
Evandro B. Costa ◽  
Baldoino Fonseca ◽  
Marcelo Almeida Santana ◽  
Fabrísia Ferreira de Araújo ◽  
Joilson Rego
Keyword(s):  
Data Mining ◽  
Educational Data Mining ◽  
Academic Failure ◽  
Early Prediction ◽  
Introductory Programming ◽  
Data Mining Techniques ◽  
Introductory Programming Courses ◽  
Programming Courses

scholarly journals A Study in the Early Prediction of ICT Literacy Ratings Using Sustainability in Data Mining Techniques

2021 ◽  
Vol 13 (4) ◽  
pp. 2141
Author(s):  
Kyungyeul Kim ◽  
Han-Sung Kim ◽  
Jaekwoun Shim ◽  
Ji Su Park
Keyword(s):  
Data Mining ◽  
Learning Process ◽  
Technology Literacy ◽  
Early Prediction ◽  
Ict Literacy ◽  
Educational Strategies ◽  
Achievement Level ◽  
Data Mining Techniques ◽  
Educational Backgrounds ◽  
Customized Learning

It would be very beneficial to determine in advance whether a student is likely to succeed or fail within a particular learning area, and it is hypothesized that this can be accomplished by examining student patterns based on the data generated before the learning process begins. Therefore, this article examines the sustainability of data-mining techniques used to predict learning outcomes. Data regarding students’ educational backgrounds and learning processes are analyzed by examining their learning patterns. When such achievement-level patterns are identified, teachers can provide the students with proactive feedback and guidance to help prevent failure. As a practical application, this study investigates students’ perceptions of computer and internet use and predicts their levels of information and communication technology literacy in advance via sustainability-in-data-mining techniques. The technique employed herein applies OneR, J48, bagging, random forest, multilayer perceptron, and sequential minimal optimization (SMO) algorithms. The highest early prediction result of approximately 69% accuracy was yielded for the SMO algorithm when using 47 attributes. Overall, via data-mining techniques, these results will aid the identification of students facing risks early on during the learning process, as well as the creation of customized learning and educational strategies for each of these students.

Creativity in CS1: A Literature Review

2022 ◽  
Vol 22 (2) ◽  
pp. 1-26
Author(s):  
Sadia Sharmin
Keyword(s):  
Science Education ◽  
Literature Review ◽  
Computer Science ◽  
Creative Thinking ◽  
Computer Science Education ◽  
Project Based Learning ◽  
Retention Rates ◽  
Introductory Programming ◽  
Introductory Programming Courses ◽  
Programming Courses

Computer science is a fast-growing field in today’s digitized age, and working in this industry often requires creativity and innovative thought. An issue within computer science education, however, is that large introductory programming courses often involve little opportunity for creative thinking within coursework. The undergraduate introductory programming course (CS1) is notorious for its poor student performance and retention rates across multiple institutions. Integrating opportunities for creative thinking may help combat this issue by adding a personal touch to course content, which could allow beginner CS students to better relate to the abstract world of programming. Research on the role of creativity in computer science education (CSE) is an interesting area with a lot of room for exploration due to the complexity of the phenomenon of creativity as well as the CSE research field being fairly new compared to some other education fields where this topic has been more closely explored. To contribute to this area of research, this article provides a literature review exploring the concept of creativity as relevant to computer science education and CS1 in particular. Based on the review of the literature, we conclude creativity is an essential component to computer science, and the type of creativity that computer science requires is in fact, a teachable skill through the use of various tools and strategies. These strategies include the integration of open-ended assignments, large collaborative projects, learning by teaching, multimedia projects, small creative computational exercises, game development projects, digitally produced art, robotics, digital story-telling, music manipulation, and project-based learning. Research on each of these strategies and their effects on student experiences within CS1 is discussed in this review. Last, six main components of creativity-enhancing activities are identified based on the studies about incorporating creativity into CS1. These components are as follows: Collaboration, Relevance, Autonomy, Ownership, Hands-On Learning, and Visual Feedback. The purpose of this article is to contribute to computer science educators’ understanding of how creativity is best understood in the context of computer science education and explore practical applications of creativity theory in CS1 classrooms. This is an important collection of information for restructuring aspects of future introductory programming courses in creative, innovative ways that benefit student learning.

scholarly journals Learners Programming Language a Helping System for Introductory Programming Courses

2016 ◽  
Vol 35 (3) ◽  
pp. 347-358
Author(s):  
Muhammad Shumail Naveed ◽  
Muhammad Sarim ◽  
Kamran Ahsan
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Retention Rate ◽  
Introductory Programming ◽  
Source Program ◽  
Definition Of ◽  
High Level ◽  
Novice Students ◽  
Introductory Programming Courses ◽  
Programming Courses

Programming is the core of computer science and due to this momentousness a special care is taken in designing the curriculum of programming courses. A substantial work has been conducted on the definition of programming courses, yet the introductory programming courses are still facing high attrition, low retention and lack of motivation. This paper introduced a tiny pre-programming language called LPL (Learners Programming Language) as a ZPL (Zeroth Programming Language) to illuminate novice students about elementary concepts of introductory programming before introducing the first imperative programming course. The overall objective and design philosophy of LPL is based on a hypothesis that the soft introduction of a simple and paradigm specific textual programming can increase the motivation level of novice students and reduce the congenital complexities and hardness of the first programming course and eventually improve the retention rate and may be fruitful in reducing the dropout/failure level. LPL also generates the equivalent high level programs from user source program and eventually very fruitful in understanding the syntax of introductory programming languages. To overcome the inherent complexities of unusual and rigid syntax of introductory programming languages, the LPL provide elementary programming concepts in the form of algorithmic and plain natural language based computational statements. The initial results obtained after the introduction of LPL are very encouraging in motivating novice students and improving the retention rate.

scholarly journals Helping to realize “computer science for all”: Student outcomes of self-pacing in introductory programming courses

2016 ◽  
Vol 8 ◽  
Author(s):  
Jaime Lester
Keyword(s):  
Computer Science ◽  
Self Report ◽  
Experimental Methodology ◽  
Classroom Observations ◽  
Control Group ◽  
Introductory Programming ◽  
Quasi Experimental ◽  
The Impact ◽  
Introductory Programming Courses ◽  
Programming Courses

Sparked by a series of national campaigns to increase interest in computer science, computer science departments are inundated with students who are interested in learning how to program. Despite the interest, introductory computer science course have relatively low completion rates (approximately 55% at Mason) and high rates of academic integrity violations. In response to this environment, the Computer Science department at Mason received an external grant to redesign their introductory programming courses to a self-paced, flipped format. Implementation began in Fall 2015 with a quasi-experimental methodology that tracks students from an experimental course and a control group (those who took more traditional introductory CS courses) over the course of the semester. Data collected includes grades on assignments, self-report surveys, and classroom observations.  The purpose of this study is to examine the impact of a self-paced, flipped curricular design in an introductory experiential computer science course on the immediate (in course) completion.   In this short lightning talk, we will present data from student surveys and classroom observations identifying any difference across the control and experimental groups. Preliminary results identify a significant increase in student completion upwards of a 20% difference across the groups. In addition to increasing knowledge of the impact of self-paced courses on student retention and success in computer science, we offer an alternative method to collect data on classroom observations via the Real-time Observation Classroom Application (ROCA). ROCA allows for efficient data collection and comparison of specific pedagogies to student engagement measures.  

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