Work in Progress: Learning to Program in a Connected World

Jian Shi Electronics & Computer Science

University of Southampton Southampton, UK

js9g09@ecs.soton.ac.uk

Su White Electronics & Computer Science

University of Southampton Southampton, UK

saw@ecs.soton.ac.uk

Abstract— The problem of teaching introductory programming is a recurrent one which has interested and challenged computer scientists over the years. It has evoked differing philosophies, has motivated new languages and fuelled ‘wars’ between supporters of different languages and approaches. Much of the discourse surrounding these practices dates from a period when learning was bounded by practical activities and assiduous use of reference books. Recent technological changes are however impacting on learners’ approaches to life and study; the Internet has not only become a very visible field for the programmer’s skills, it is also plays an intrinsic role in the practices and experiences of novice learners. However academics engaged in instructing these courses, although highly computer literate may have limited personal experience of integrating independent learning via the web as a novice programmer.

This account of work in progress presents a preliminary study which explores the learning practices of students enrolled on introductory programming courses. A mixed methods approach using quantitative and qualitative data is designed to triangulate information order to reveal practices, beliefs and attitudes to learning. It focuses on discovering what the student believes, experiences and does. The paper will present interim findings and discuss the challenge and potential advantages of working within a mixed methods research framework.

Keywords—learning to program; computer science education; mixed research methods.

I. INTRODUCTION This paper presents a work in progress which is making a

detailed study of first year undergraduates learning to program. The study is being conducted in a large research-led university in the United Kingdom. Typical cohort size for this class is 145. As is usual for the UK, students specialize in their degree major from the first year of their study. Students are all high achievers, who in the majority of cases have specialized in science and technology subjects prior to university. The cohort contains a mix of students following computer science (n=100); software engineering (n=18) and Information Technology (n=27). All degrees are accredited by the British Computer Society, and broadly follow the ACM curriculum. The term spans 15 weeks and the taught component lasts 10 weeks. On a weekly basis, students are expected to attend 2 lectures (20 hours) participate in 2 hours of laboratory work. There are 3 formative activities; one every three weeks. There is a final

three-hour ‘open web’ examination. Students are expected to spend around 10 hours per week studying. Formal teaching occupies 40% of their time, the remainder is notional hours for private study. It is recognized that there is variability in students’ prior experience and confidence levels, and for that reason a long established scheme of differentiated teaching underpins this approach [1]. Other subjects which the students study in parallel with this module include Computer Systems, Data Management and Foundations of Computer Science.

Biggs identified three different levels of understanding valuable when planning the educational experience taken from a teacher’s point of view. The most valuable, he suggests is Level 3: Understanding “what the student does”. For this study, Biggs’ perspective helps define the objective of the research questions. The hypothesis is that that students who learn to program in today’s highly connected world, may be adopting different approaches to those favored by previous generations. Furthermore current teaching is predominantly informed by practices and beliefs formed before the era when the World Wide Web and the Internet played a significant role in everyday information seeking practices. Therefore insights in this area may be of particular value. The research questions addressed include:

1) What effect does a students’ background, attitudes, and beliefs have on their subsequent approaches and practices when learning to program?

2) Whilst learning to program to what extent do different students?

a) Change their expectations of achievement b) Gain or loose confidence and motivation c) Modify their approaches to learning as they

progress? 3) How do students integrate their formal and informal

learning activities? To what extent do students a) Rely on formally provided materials and exercises? b) Develop individual approaches to learning which

integrate real world and online activities and materials?

c) Integrate their learning of individual programming concepts into generalizable approaches?

Faculty routinely modify their approaches to teaching according to their working context. However it may be possible to systematically use the information collected in this research

2013 Learning and Teaching in Computing and Engineering

978-0-7695-4960-6/13 $26.00 © 2013 IEEE

DOI 10.1109/LaTiCE.2013.48

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2013 Learning and Teaching in Computing and Engineering

978-0-7695-4960-6/13 $26.00 © 2013 IEEE

DOI 10.1109/LaTiCE.2013.48

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to identify, and then implement structured changes to the curriculum, the impact of which can be monitored and evaluated in future academic years.

Section II presents a review of current UK higher education background and wider literature, in section III methodologies are explained. In Section IV, the design and implementation of a pilot study and a running experiment will be described and analyzed. Section V concludes the findings and identified future study plans.

II. BACKGROUND Every academic year, thousands of new students begin their

journey of studying computer related degrees at universities with an introduction computer programing. In the UK in the 2012/13, academic year 60,385 new full-time students registered for the subjects relevant to computer science according to statistics from HESA (Higher Education Statistics Agency). The backgrounds and pre-experience will vary. Changing practices in learning, especially increasing widespread and sophisticated use of the web are observed. It would be helpful to understand the nature of these changes, if the curriculum and teaching practices are to be most effective. This study seeks to gain some insights to help in that process.

A. Previous Related Work

Knuth started to focus on this problem in 1974 [2] and Wirth went on to introduce Pascal as the gateway programming language for novices in 1996 [3]. Subsequently, more detailed studies and findings were published. Jenkins used toys for motivation and engagement purposes [4]. Academics from different UK institutions paid attention to the reason why a small student cohort failed in their final assessments [1] and the learning attitudes & behaviors of our high performing students [5]. Cook suggested that teachers should consider semantics and programs themselves as an object of study [6].

Interested groups have also been engaged in this area for a long period of time. The ACM Special Interest Group on Computer Science Education (SIGCSE), was founded in 1968 and has run an annual conference in the US since 1987, focusing on the entire range of issues associated with computer science education. For the past three years (2010 - 2012), one fifth to a quarter of the papers were about learning/teaching how to program. Academics shared their innovations for motivation and engagement such as musical composition [7], surveys conducted for strugglers for the purpose of helping them learning to program [8], and the idea of separating our students into different groups according to their learning paces [9]. ACM SIGCSE’s associated Innovation & Technology in Computer Science Education (ITiCSE) conference was established in Europe from 1996. It has paid more attention on learning to program with about half of the published papers are discussing relevant topics in recent years. In 2010 & 2011, the ITiCSE working group “Motivating Our Top Students” & “Motivation All Our Students” have analyzed and summarized the teaching strategies across institutions from all over the world (especially UK and US) and findings generated from the results of extensive surveys [10,11], including the benefits of streaming teaching, how to meet student expectations and

broaden their research experiences, ways of maximizing individual potential and making interdisciplinary connections.

B. Biggs Levels of Understanding

Biggs observed that “the way we go about accomplishing learning will of course depend on what we conceive learning to be” [12]. Therefore, academics should understand what teaching is. He suggests a framework of teaching strategies and modeling student learning [12] where optimally academics focus on “what the student does” (Level 3) and shape their teaching accordingly. This work in progress is aiming to study what our students do whilst they are learning to program, such as their learning experience and behaviors. In this case, it is necessary to understand our students’ learning process first.

C. Kolb’s Experiential Learning Cycle

Many models of learning support a constructivist approach. Kolb’s “Experiential Learning Cycle” can be viewed as a constructivist philosophy showing learning as a transition of “creating” knowledge from experience [13]. Taking such a viewpoint and observing the way in which teaching of programming at Southampton is currently structured we observed that activities could be analyzed based around Kolb’s learning cycle. Specifically, expanding on the elements of the cycle:

� Experience: Involvement in experiential activities, e.g. code review, live programming demonstration and practical coding from labs, coursework or examination.

� Reflection: Observation and thinking from actual perspectives, e.g. group discussion; “receive” knowledge in lectures.

� Abstract: Conceptualization, probably through integrating theories introduced in lectures.

� Experiment: Establishment of the problem-solving ability by adopting theories that have been learned, possibly in the means of practical work such as labs, coursework or examination.

Apart from these four main elements, private study is also expected. Such informal learning activities may include getting help online and chatting with friends, etc., which could help students go through the whole learning cycle more smoothly.

D. Motivation

Since “motivation is the key” [10,11], de-motivation might lead to failures in the learning cycle, undermining learning to program. Two important factors that might cause reduced motivation include locus of control and learned helplessness.

Locus of Control Locus of control [14] is defined as the views of human

beings towards the forces that influent peoples’ lives and destiny, which can be divided into internal and external. Internals (those who demonstrate internality) believe that the activities (include learning) and the results are determined by the internal factors, implying that their abilities and intentions are able to control the learning process; whilst externals think they are forced by destiny, luck, chance and other people. Different locus of control held by learners will affect their

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learning. The learners’ perceptions will affect achievement, motivation, the input effort, attitude and performance of the task. Different learners will have different sensitivity towards rewards and the meaning of punishment and scores. It will also affect their sense of responsibility and their attitudes towards and trust of teachers.

Learned Helplessness The concept of learned helplessness defined as failing to

respond to repeated failure or punishment [15]. The helplessness and the unreceptiveness is a negative psychological phenomenon ‘learned’ and caused by repeated failure and torture instead of innate instinct. The main source of learned helplessness is what individual believes to cause the situation. There are more possibility for individuals to suffer from depression and low self-esteem when they believe that the internal steady and uncontrollable factors caused the study and psychological problems. They will take it for granted that it is impossible to enhance academics performance, which will cause lower motivation to study and a failure to try.

The study explained below describes and analyses a pilot study designed to surface aspects of students’ beliefs, attitudes and behaviors taking into account the existing literature cited above. Subjects’ responses were elicited reflecting on their experience of learning to program during an introductory programming principles module. The subjects are a target cohort of 142 students. The pilot survey was conducted towards the end of the academic year and elicited a very low response rate. Subsequent studies will be conducted in parallel with the learning process during the 2012-13 academic year.

III. METHODOLOGY The study has been designed with mixed method approach

for the combining quantitative and qualitative methods. The pilot survey and subsequent cohort wide surveys provide basic data in answer to some of the research questions. Additional data will be collected from the students using individual and focus group interviews and a nominal group technique study. Using mixed methods has the advantage that it enables the design to anticipate and remedy what might otherwise be some gaps in the data collection. These instruments will be used provide data directly required by the research questions not covered by the survey. They will also provide a means to drill down and to determine clearer interpretation of some of the survey findings and to triangulate the data seeking complementary or contradictory responses or data which clarifies the nature of variability of responses within the cohort. In particular explanations of current informal learning practices, and the use of web based resources or learning networks will be examined in this later stage.

The primary researcher will also note and collect contemporaneous observations and discuss observations and experiences with the group of post-graduate demonstrators who have regular contact with the students.

IV. DATA COLLECTION

A. Pilot Survey

This pilot study was established in the form of questionnaire in May 2012 (AY2011-12) and lasted for two weeks. The main purposes of this study were

a) obtaining a general understanding about what factors are important to undergraduate students when they first learn to program at universities;

b) trialing questions to shape future formal surveys from the responses.

Apart from the basic personal information such as the gender and prior programming experience, the questionnaire examined four parts of the standard teaching processes in the UK – lectures, assessments, feedback and private study.

Interesting findings have been gained in some level in terms of students’ perception of the connection between their learning approaches and outcomes through reflecting upon the responses.

� Many novice respondents thought it was hard to understand some basic concepts when starting to learn to program. Most of them could sort this problem out later but the learning progress was slightly delayed.

� Due to the confusion about the testing scripts, students were struggling with “testing and debugging” rather than object-orient programming theories such as inheritance and polymorphism. The latter topics were considered to be really challenging as well, but not as much as the former.

� Most respondents preferred live programming demonstrating such as in-class demonstration and online videos as a rapid way to learn to program.

� Respondents were generally held a positive attitude to the formal learning opportunities provided by practical labs and coursework would promote their learning.

� Concerned that the lecturers might consider them to be not hard working, strugglers preferred to turn to demonstrators, their friends or search the Internet for help.

B. Initial Survey

The initial survey was conducted in the form of questionnaire in September 2012 prior to teaching beginning. It aimed to gain an overview of how much prior experience our new students had and their initial attitudes towards learning to program, including whether they were motivated and their beliefs about how difficult they assume programming to be.

Among the 169 completed responses, over a half of new students indicated that they had a little prior programming experience. About 95% of the cohort agreed that they were motivated, considering programming not a difficult task and would work hard to master the exam, in which two thirds believed they were highly motivated.

C. Weekly Survey

This survey was scheduled weekly between October 2012 and December 2012, aiming to trace students’ learning

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attitudes. This is a short online survey, where students are invited to provide responses while signing out of weekly practical labs. Questions were designed to be short and easy to answer (just simply tick any that apply), including their attitudes towards programming (how much do they like or dislike it) and their expectations (what grade they could get in final exam). The main objective of this survey is answering the second and some of the third research questions.

The response rate is 77% (112 out of 145). Having analyzed the responses, following findings could be generated:

� Similar to the findings from the initial survey, “Testing & Debugging” is still considered to be a huge challenging topic. Approximately 41% (59 out of 145) responses commented on that task to be difficult, harder than their expectation or challenging.

� Students’ learning is strongly reliant on formal exercises. During weekly observations, all those interviewed argued that they did not care about the learning approaches they used or how to have them modified. All they wanted to do was follow the provided labs and coursework.

� Students’ perception of expected achievement fell when a) they considered lab specification difficult to understand and they worried that this was a problem which might recur during future tasks and in their career; b) they were struggling so much with one concept that it delayed the planned or scheduled study which followed.

� Students remained highly motivated after they successfully managed to have a sound understanding of one theory no matter how ‘struggling’ they rated themselves overall.

D. End of Term Survey

This survey was conducted late in the term immediately prior to the Christmas vacation. The study aimed to investigate how the students adopted the Internet to help their programming learning via an online questionnaire. The questions are derived from those trialed by pilot study. By the time of writing, the respond rate is 32% (46 out of 145). It is really satisfactory since the students were busy preparing their final examinations. Preliminary analysis identified heavy use of online approaches. Students considered the Internet indispensable for their study. They used it before, during and after lectures/labs and their favorite platforms are public searching engine such as Google and formal provided online platforms, because they thought the Internet is convenient and it is the best place to find information without worrying asking “silly” questions.

V. CONCLUSION & FUTURE WORK The pilot study collected a small amount of data, illustrating

the importance of timely questionnaires and brief surveys. However a more sizeable volume of rich data is needed to provide adequate information for detailed analysis and informed discussion. Although it is understood anecdotally that students encounter problems and experience some variability in motivations this was not reflected in the gathered pilot data. For this reason the strategy of weekly tracking of student progress was considered a more effective instrument, although

such weekly surveys would necessarily need to be short and easy to complete. A more detailed online survey at the end of term, and a further survey after students receive their exam results are proposed.

It was anticipated that, having engaged students in the process of tracking their progress it might then be easier to recruit students to provide more detailed insights through interviews and focus groups. Nominal Group Technique however is more likely to be successful in gaining feedback from a larger percentage of the entire cohort albeit that the breadth of data in this case may be less. Contemporaneous observations and structured reflections from the post-graduate demonstrators will be used to formalize observations which are currently anecdotal.

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[3] N. Wirth, “Recollections About The Development Of Pascal,” in History of programming languages---II, T. J. Bergin Jr. and R. G. Gibson Jr., Eds. New York, NY, USA: ACM, 1996, pp. 97–120.

[4] T. Jenkins, “A participative approach to teaching programming,” in Proceedings of the 6th annual conference on the teaching of computing and the 3rd annual conference on Integrating technology into computer science education: Changing the delivery of computer science education, 1998, vol. 30, no. 3, pp. 125–129.

[5] J. Carter, N. Efford, S. Jamieson, T. Jenkins, and S. White, “The TOPS Project – Teaching our Over-Performing Students,” in 8th Annual Conference of the Higher Education Academy for Information and Computer Science, 2007.

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[13] D. A. Kolb, Experiential Learning : Experience as the source of learning and development, no. 1984. Prientice-Hall, 1984.

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[15] C. Petersen, S. F. Maier, and M. E. P. Seligman, Learned Helplessness: A Theory for the Age of Personal Control, vol. 3, no. Supplement. Oxford: Ovford University Press, 1993.

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