Keywords

1 Introduction

Computer programming is difficult for students to master because of its complexity. This includes learning the syntax of the language, the use of the Integrated Development Environment (IDE), problem-solving strategies, testing strategies and coping with errors. This paper focuses on how students cope with errors and their resulting problem-solving strategies. In order to master the skills of programming, a student needs to persevere to fix the many different errors and mistakes. The logic in programming is like mathematics where the skills accumulate over time with each concept building on previous concepts [1].

Students developing programming projects are often frustrated when they encounter errors and find difficulty in completing complex programming tasks. Programming, in itself, is difficult and requires discipline with constant practice. Students need to seek out alternate strategies [10] and be prepared to fail without reacting negatively. This trait is known as grit, i.e. passion and perseverance for a long-term goal, which can predict success over and above intelligent quotient (IQ) [6].

Linked to the lack of grit is the students’ perception of their intellectual ability as being fixed and their failure to achieve as something they cannot control [1]. Students with a growth mindset who believe that their intelligence can be changed with perseverance and effort will, more likely, succeed. Learning to program can easily produce a fixed mindset [5] since there are so many ways a student can get stuck which can induce a student to give up. Students with a growth mindset are more likely to employ alternate strategies to address their problems as the problems arise.

An important factor in this process is the use of praise and feedback. Students who are praised for their efforts as opposed to their intelligence and ability are more likely to focus on developing their skills by mastering new materials [11]. The use of constructive and formative feedback to increase motivation [9] and guide the student to the solution has been proven to produce positive outcomes.

Little research has been done that combines grit and growth mindset in high school students whilst they develop a significant programming project in South Africa. This paper explores how grit and growth mindset influence/shape the learning of high school students in a programming project (PAT). We measured academic performance, grit and mindset, number of submissions and conducted interviews with a subset of the students participating in the project. A mixed methods approach [4] is used to analyse the data.

2 Literature Review

2.1 What Is Growth Mindset?

In a study of junior high school students in a mathematics course, Blackwell et al. [1] showed that adolescents’ beliefs about their intelligence inform their motivation for achievement. Some students believe that intelligence is fixed or unchangeable, (fixed ‘entity’), which is termed an entity theory. Others believed that intelligence can change and be developed, which they termed an incremental theory. Blackwell discovered that students who had a more incremental theory of intelligence had a distinct advantage over those with a more entity theory of intelligence stance; and had achieved better results in their first year of junior high [1]. The adolescents who endorse an incremental theory of intelligence held stronger learning goals and held a positive belief about efforts, made more positive statements about their ability and created strategies based on efforts in relation to failure which as a result boosted their achievement in mathematics.

Cutts et al. [5] used a growth mindset approach to teaching programming with first year university students in an introductory programming course over a six-week period with test scores being used as a measure of effectiveness. They discovered that when students struggle with programming problems, they can develop a fixed mindset unless they are encouraged with alternative strategies. After six weeks, there was a positive effect for those who received growth mindset training. On the average, people who were taught about mindset showed a shift toward a growth mindset and those who were not taught about mindset showed a shift toward a more fixed mindset during the course [5].

2.2 What Is Grit?

Grit overlaps with but is different to mindset. According to Duckworth et al. [6], grit is a non-cognitive quality that emphasises the long-term stamina of an individual who will finish tasks and pursue an aim over a period of years. Grit is not a single entity; it is made up of efforts and continued interest despite failure or adversary. The study of grit as predictor of success has been developed to include a grit scale which is a tool to measure grit in individuals [7].

While there is a vast amount of research relating IQ to academic achievement, there is far less on the non-intellectual strengths of an individual compared to his/her academic achievement. Little is known about other factors that could predict academic performance. In studying why some individuals accomplish more than others with similar intelligence, there is need to consider other attributes of an individual [6]. Research has indicated that individuals identified as possessing grit often seem to demonstrate sustained efforts and interests over many years regardless of failures and setbacks. As examples, they found that IQ was less of a predictor for academic performance than self-discipline in a longitudinal study involving the 2005 Scripps National Spelling Bee and freshman candidates who entered the United States Military Academy, West Point, in July 2004.

2.3 Scaffolding Combined with Feedback

Feedback is significant when a student is developing a project as it forms part of formative assessment. The student is able to answer questions like [2]:

  • What knowledge or skills do I aim to develop?

  • How close am I now?

  • What do I need to do next?

With the use of the adapted rubric provided by the Independent Examination Board (IEB), a grade 12 assessment body, which clearly denotes the skills and level of competency required at each stage, students can determine their success in the project they are programming. Feedback needs to address cognitive and motivation factors. This leads to the feeling of having control over their progress, which could be the motivational factor [2].

Contemporary learning theories support two ideas, namely [12]: that knowledge is constructed, and that learning and development are processes that are embedded in our culture and supported socially.

Scaffolding and formative assessment help move a student through a zone of proximal development (ZPD) [13]. Scaffolding is the support given by teachers to students in the form of hints, encouragement, and reminders to ensure the successful completion of a task.

In a study conducted on teaching software engineering to 16-to-18-years old high school students, the importance of positive feedback in increasing motivation was emphasized [9]. The researchers recognised that motivated students can outperform a more talented student with less motivation. They linked motivation to interests in the topic with the teacher assessing whether the choice was feasible and the additional skills required for students to be able to develop their project [9]. The gap in their knowledge was bridged by scaffolding in the form of tutorials and articles.

In programming, students will frequently experience problems with their coding; either in syntax, run time or logical errors. Successful students will employ a repertoire of strategies to get ‘unstuck’ when programming [10] linked to this success is the ability to persevere when coding problems occur. A student may need to use a variety of strategies, such as [10]:

  1. 1.

    getting help from other sources (peers, the Internet, and books);

  2. 2.

    working on similar examples;

  3. 3.

    trying to understand the problem by representing it using diagrams or breaking it down into smaller parts; and lastly

  4. 4.

    by ‘using the force’, which is described as the student telling him/herself to remember, think and persevere.

3 Study Design

3.1 Study Setting

This study was performed in a private Catholic school which highly values academic achievement. The school is located in a wealthy area of a large South African city and most, if not all, participants come from affluent families. Most students are white with a few Asian, Indian and Black students. By the start of this project the boys were familiar with the programming concepts taught previously and were able to code objects, arrays of objects, a basic GUI in Java and create a database in Microsoft Access. The students had basic programming skills to debug code, fix run time and logical errors for small programs.

Whilst debugging a program is important, this skill was not measured, only the grit and perseverance when debugging a program will be measured. Students may improve their debugging skills during the study, but this result will not form part of the study.

3.2 Mixed Methods Methodology

Mixed methods design is a research design for collecting, analysing and reporting research by integrating both quantitative and qualitative data [4]. Mixed methods gather both quantitative and qualitative data, integrates both types of data and then draws interpretations on the combined results to understand the research problem. By combining both quantitative and qualitative data the assumption is that combined strength of both data will provide a better understanding of the problem [3].

In January 2015, there were a total of twenty-nine students studying programming divided into two classes. The one class was taught by the researcher (14 students) and the other by a colleague (15 students). The students were in their second year of their three-year course and were taught programming structures such a simple data types, sequencing, selection and iteration statements in Java.

In the third term of 2015 the students had to code their own projects using a topic of their own choosing and this was assessed by the adapted IEB rubric. After the requirements had been established, students developed their projects in sections. Students designed, coded and tested each section (Graphical User Interface, classes, database) before moving on. The project was developed over a six-week period with students attending seven periods of thirty-five minutes long per week. The project was assessed at the end of their grade 11 which formed the foundation of their grade 12 project. The PAT has a significant weighting of \(25\,\%\) of the year mark. The mark for the PAT depended on the specification, design and the functionality of the code.

3.3 Quantitative Data

The students were assessed using the grit short-scale questionnaire [7] and an adaptation of the growth mindset questionnaire [8]. They were assessed at the beginning of the project, after they had completed their design and at the end once their project was completed. The three scores for grit and the three scores for mindset produced by each student were averaged to produce a single grit score and a single mindset score. In addition, the number of submissions of each student was also recorded. Each time their project was assessed, the score was updated on the mark sheet by the teacher. In most cases the teacher assessed the project in the presence of the student ensuring the student had immediate feedback detailing where they went wrong and what they could do to improve. The students’ average grit score, average mindset score, their number of submissions and their final PAT result were recorded in a spreadsheet.

3.4 Qualitative Data

Using the quantitative data, 6 students were identified to be interviewed. The purpose of the interviews was to understand the lack of correlation between the grit, mindset and PAT results. The students were asked questions to identify their process when they found errors and whether they gave up or persevered when they encounter errors.

4 Results

Students did very well; only 2 students achieved below \(80\,\%\) (most scored \(100\,\%\) for the project). This narrow range of scores makes it difficult to differentiate between the students’ scores. Table 1 summarises the quantitative data in terms of grit, mindset, number of submissions and the PAT scores while Table 2 examines the correlation coefficients.

The strongest correlation was between the number of submissions and PAT score with a correlation of 0.52. The correlation between PAT, mindset and grit was weak at 0.13 and 0.48, respectively. The correlation between grit and the number of submissions was even weaker at \(-0.06\). The strongest relationship was determined between number of submissions and the PAT results with \(r(29)=0.52\) and the significance of this relationship is determined by a p value of 0.002. The correlation between grit and the PAT was \(r(29)=0.48\) with a significance of \(p=0.004\). These results imply that both grit and the number of submission are related to the PAT scores. To investigate these findings six students were interviewed — their results are shown in Table 3.

Table 1. Results of quantitative data
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Table 2. Correlation coefficients (CC)
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Table 3. Results of students interviewed
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All the students interviewed faced problems during the coding phase. All students displayed perseverance by devising problem-solving strategies to correct their code. The problem-solving strategy chosen was personal to each student. Student A and Student E both achieved \(100\,\%\) with 6 to 8 submissions. Both students did not ask their classmates during class or use the WhatsApp group but instead traced through their programs to find their errors. Student A was an extremely shy student who did not like asking for help in class. Student E did not want his classmates to think he could not solve the problems; so, he persevered by himself. Student E is a high-achieving student who has academic, sporting and cultural colours and was selected to be a leader in the school. He enjoyed the challenge of the project and used the teacher’s advice, the internet as a resource when he was experiencing problems with his coding. He also traced his program to locate the errors. Both boys found the deadlines motivational in terms of submitting on time and encouraging to keep their project on track.

Student D persevered by tracing his program on paper and asked friends and family for help when he was stuck while Student F researched the internet. Student F also asked classmates and the teacher for help whenever he was stuck. Both of them found the deadlines motivational and used the multiple submissions to improve their marks.

Student C devised a system of coding multiple solutions to each problem. Using these solutions, he chose what he considered to be the best solution and then moved on from there. He found difficulties in keeping track of the versions of his solutions. His method was time consuming; however, he was still able to submit his PAT five times.

Student B alternated coding his solution with a computer game. Each time he was stuck on either project, he switched to the other. Student B was not able to successfully separate the working code from the front end. Most of his logic was in the front end; and once on this path, he could not move the code and still have a working solution. He did, however, persevere in getting the code to work by tracing his program and explaining his logic to his father. He admitted to frequently procrastinating; although, he submitted his PAT seven times.

The qualitative data revealed that each student persevered when problems were encountered although this is not reflected in their grit and mindset scores.

5 Conclusion and Future Work

Upon initial investigation, there appears to be little relationship between grit, mindset and the PAT scores. However, upon further investigation into the qualitative data, grit can be seen by the perseverance displayed by the students. Students did not give up when they encountered errors and went on to develop problem-solving strategies to fix their errors. The deadlines served to motivate the students and kept them on track with their projects. A possible reason for the lack of correlation between the grit, mindset and PAT scores could be the students’ immaturity in completing the questionnaire or their fixed mindset in that they considered themselves to already be very intelligent, which is supported by their PAT results. The sampled population was skewed toward a more affluent demographic together with an existing motivation to achieve good results.

This study could be enhanced by investigations into the problem-solving strategies developed by the students. Since no problem-solving strategy was taught, there is clear evidence that the problem-solving strategies were developed independently by the students and each were varied. Studies could be conducted to determine whether teaching a particular problem-solving strategy would be beneficial as opposed to students developing their own. Since the sampled population was skewed towards the more affluent demographic, further studies could be performed in government schools, among female students in single-gender female schools with a more diverse race groups; and in schools where the class average is lower and with a wider range.