Causal attributions of success and failure made by undergraduate students in an introductory-level computer programming course
Introduction
The purpose of this research is to identify the causal attributions of business computing students in an introductory computer programming course, in the computer science department at Notre Dame University, Louaize. This goal is deemed important to practitioners by many authors (Alderman, 2008). Particularly, it is important to the researcher who has been teaching computer programming for more than 10 years. As an educator himself, he has a special interest in learning more about motivation of his students (Stake, 1995). As a teacher, he is committed to supporting his students in the successful completion of their computer programming courses. Further, academic achievement is a central concern at Notre Dame University, Louaize (Rahi, 2005).
The study outcomes can be used to suggest ways to energize unmotivated students such as attribution retraining programmes to provide better learning opportunities (Hammersley & Gomm, 2000). Knowledge of causal attributions and their underlying properties at an early stage of a course may help teachers use intervention strategies with students at risk of low achievement, especially those who hold self-defeating attributions. Hence, for a computer science department, the present study is crucial to improving teacher effectiveness and student learning.
Forty-five students volunteered to share their cognitive and affective experiences with the researcher. The majority of participants were males as was the business computing programme’s population from which the sample was drawn and as was the computer science department’s population which offers the programme. Participants’ ages ranged from 19 to 26 years with an average of 21.7 years. The majority of participants were Lebanese as was the case with the business computing programme, the computer science department, and the University. To a great extent, the profile of the sample matched up with the population’s profile.
Section snippets
Causal attributions
It is important to find the causes that students ascribe to an achievement outcome, such as passing or failing a course. The main reason is that causes play a major role in moulding future expectancies and emotions of learners that is their motivational states. The latter, in turn, determine learners’ achievement strivings (Griffin, 2006). Causal ascriptions for an event may vary from one individual to another (Dörnyei, 2001, Elliott et al., 2005). The original attribution model (Weiner et al.,
Scarcity of research
As yet, there are no studies in Lebanon that support or deny the findings reported in the previous paragraph. Thus, this research and its findings will fill in gaps to present knowledge of motivation in the Lebanese context. In addition, while there are studies that examined causal attributions for achievement in subjects such as Mathematics (Bornholt & Möller, 2003) and English (Williams et al., 2004), there is none in the computer programming discipline. The main evidence of the scarcity of
Qualitative epistemology
Learning from business computing students themselves what they have constructed about their motivation from an attributional perspective is the basis for the understanding that this research seeks to provide. The study starts by listening to students about their lived experiences when they received their grades in the ‘Computer Programming 1’ course (Prior, 2004). Qualitative research is best fitted for this study since precise and substantial descriptions of the students’ experiences from
The interview method
The first stage in designing the interview consists of selecting its type. Two factors guide this selection: the purpose of the interview and its structure (Kvale, 1996). Since the main purpose of the study is to identify students’ causal attributions, open-answer format questions allow for open responses such as views, perceptions, and experiences (Mertens, 2005). Participants were persuaded to freely talk about their experiences within the framework of this research (Adler & Clark, 2008).
Data analysis plan
Data from transcriptions, and demographic forms were organized in one electronic plain text file for each participant. Each file had the .txt extension and a name that identifies the interviewee. All 45 text files were stored in one folder, which was backed up. While each textual source file was read through carefully using HyperRESEARCH, codes were assigned to parts whose meanings fell within the research framework (Stake, 1995). HyperRESEARCH is a software tool for qualitative analysis used
The process of analyzing the research data
The analysis of data started with the 45 text files which were changed to read-only status to protect them from being edited. When HyperResearch was launched, it started with a blank study that was named using the phrase Attribution Theory and the creation date. This study created a Case Card that was named using the first name in the list of interviewees. Then, the text file that contained what this interviewee said was opened. At this stage, the text file became the source file of a Case
Research findings
The causal attributions of achievement outcomes in ‘Computer Programming 1’ made by business computing students were 10 in all (see Table 2 below). ‘Learning strategy’ was the leading causal attribution and ‘lack of study’ came in the second place. An interesting finding was that the least cited cause was ‘lack of effort’. While 35 participants made one causal attribution, 10 participants made two causal attributions (see Table 3).
Extract 13 below shows how participant 27 attributed his causal
Causal attributions made in this study compared to previous research
The search for the causes of computer programming achievement outcomes of the 45 participants led to the identification of 10 causal attributions: ‘learning strategy’, ‘lack of study’, ‘lack of practice’, ‘subject difficulty’, ‘lack of effort’, ‘appropriate teaching method’, ‘exam anxiety’, ‘cheating’, ‘lack of time’, and ‘unfair treatment’ (see Table 2). Of the 10 causal attributions, only ‘subject difficulty’ and ‘lack of effort’ were amongst the four causes – ‘ability’, ‘effort’, ‘task
Limitations
An important limitation of this study is its small sample size. Also, the participants were not selected randomly (Adler & Clark, 2008). In addition, the study followed a qualitative orientation. Therefore, it was subjective. Furthermore, validation of the transcripts was influenced by the fact that some of the students were more proficient than others in English. The translation of interviews from Arabic to English could have been different had it been carried out by another person. The same
Worldwide applicability
This research paper supplements the worldwide limited pool of literature on educators’ understanding of students’ motivation to learn computer programming. The results challenged a long held conviction that associates motivation with ability, effort, task difficulty, and luck. This study challenges this conviction in the computer programming discipline. Thus, the study’s results have worldwide significance because computer programming is a universal discipline. The results are expected to have
Conclusion
The purpose of this research was to determine the causal attributions made by business computing students in computer programming in the computer science department at Notre Dame University, Louaize. The importance of this study stems from the scarcity of research on motivation of undergraduate students studying computer programming in Lebanon. Also, understanding motivation in achievement contexts related to computer programming from an attributional approach worldwide is almost non-existent.
Recommendations for future research
In light of the existing literature and this study, some gaps in the understanding of motivation in learning computer programming from an attributional approach in computer programming were identified. It would be worthwhile to cover those gaps by conducting further research based on the recommendations below:
- 1.
Future research should include participants from other programmes that offer introductory-level computer programming courses, from different universities residing in various geographical
Acknowledgments
The author sincerely thanks all Business Computing students who volunteered to participate in the study, and Notre Dame University, Louaize.
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