Student-Lecturer Interactions during First Year Computer Programming Tutorials:

1. Student-Lecturer Interactions during First Year Computer Programming Tutorials: Towards a model to help guide new lecturers Mark DixonSchool of Computing & MathematicsUniversity of Plymouth, UK

2. Introduction - Background • programming widely recognised difficult to learn and teach • recent student numbers increase • doubled 2 years ago • PhD student teaching increased • need to maintain teaching quality Introduction Method Model Results Conclusions

3. Introduction - Background • problem • (students come with impression that computers are intelligent) • cause • GCSE syllabus • Marketing • Films Introduction Method Model Results Conclusions

4. Introduction - Aims • model of lab-tutorial student-lecturer interaction • experienced lecturer behaviour? • student behaviour? • hazards, beneficial, inhibiting? • passed onto new lecturers • literature: limited observations of student-lecturer interactions in lab tutorials Introduction Method Model Results Conclusions

5. Introduction - Objectives • How do we interact with students? • how do we get inside their heads? • need explicit (evidence-based) model • How do we pass this on to new lecturers? • need explicit strategy • Teaching and Learning Courses • good for generic Learning Theory • very little / no discipline specific Introduction Method Model Results Conclusions

6. Method: Overview • Develop initial model • single lecturer's anecdotal experiences (over 15 years) • Observational Study • participant observation &audio recordings • during stage 1 programming tutorials (in labs) • transcription of audio • QDA to identifyrecurrent / key themes Introduction Method Model Results Conclusions

7. Method: Observation Protocol • Short Briefing (Investigators, Aims, Process, Ethics) • Consent Form to all studentsindicate willingness -> fill in form • Conduct tutorial normally(location, duration, attendance, resources, content) • Students proceed with exercisesAsk for assistanceLecturer responds(if consent then audio record) Introduction Method Model Results Conclusions

8. Initial Model: Questions, Understanding, Process • provide student with minimum assistance, which enables them to solve problems themselves • by asking them questions • focus on: • increasing student understanding,not completing tasks / exercises • processes used to develop solutions,not solutions themselves Introduction Method Model Results Conclusions

9. Initial Model: Broken Code Panic • Students • try code • code does not work • panic: delete code (BCP) • ask for help • Lecturer • needs to see code that does not work • gives clue to student understanding Introduction Method Model Results Conclusions

10. Initial Model: Error Message Panic • Students • type in code • run code • error message appears • panic: frantically click to get rid of error message (EMP) • ask for help • Lecturer • don't panic • read message (cute fluffy friends) Introduction Method Model Results Conclusions

11. Initial Model: Difficult Concepts var x; var y;x = 3;x = 6;y = x + 2 L: What is x? S: It gives error, x can't be 3 and 6 at the same time. • Misunderstanding stuck Introduction Method Model Results Conclusions

12. Initial Model: What vs. How S: Can you explain this code? L: Yes, it puts a zero in each element of the array • May give false impression • impressionist painting not sequential • Domain vs. Program level [Pennington] Introduction Method Model Results Conclusions

13. Initial Model: Computer Intelligence • Students • perceive computer as intelligent • approach programming like conversation with another person • type code without understanding • believe computer understands • 5 lines not working, add 400 • Lecturer • reinforce idea ofmechanistic (stupid) computer Introduction Method Model Results Conclusions

14. Initial Model: Task Focus S: Can you help me? L: Yes, what are you stuck on? S: How do you get it to … ? L: OK, which bit of code does …? S: [no response] L: OK, let's have a look at your code … how does this work? S: [no response] • Seemed to expect solution • Code seemed quite advanced, confusing, • Student could not explain code. • Eventually, admitted - did not understand it. • They typed it in, but other tutor guided them(effectively told them what to write). Introduction Method Model Results Conclusions

15. Initial Model: Cold Reading • Cold Reading L: 'What is the value of k [Boolean]?' S: 'True' [quick, confident] L: 'Are you sure?' S: 'False, I knew that!' [quick, defensive] • student guessing, reading lecturer's response (words, tone, expression) • inaccurate impression of student understanding Introduction Method Model Results Conclusions

16. Initial Model: Guidelines • Lecturer • do not touchstudent's keyboard or mouse(no 'little bit of magic') • view as diagnostic process (identify conceptual sticking point) feedback • different example for explanationsleave student to apply understanding to original problem • don't let them use you as a resourceget (help) them to do it Introduction Method Model Results Conclusions

17. Initial Model: Time Consuming • Once practiced • 1:1 easy • Very time consuming • difficult with large groups • Risk – other students wait, get frustrated, leave / stop attending Introduction Method Model Results Conclusions

18. Results: Direct Observation 1 • Saw student struggling • offered help • they accepted. • Asked how much they understood • they said just the html. • Asked did they attend the lecture – no they didn’t. • Lecturer reacted neutrally to this. • They actually understood more than thisThey had created another image, and copied the Main procedure (with the movement code) – changing it for the new image tag id.This did not work as there were now two Main procedures. • Lecturer informed them that 'you can’t have two procedures with the same name, but you can add more code to the existing Main procedure – join them together'. • Student did this – it worked Introduction Method Model Results Conclusions

19. Results: Direct Observation 2 S: Asks for help regarding SQL LIKE statement L1: Gets their SQL reference guide and looks it up, then tells student what to type S: What does the percent mean? L1: It's a wildcard character. S: Looks very confused L1: Asks for help from L2 L2: Percent means any characters. For example d% picks things starting with d, and %z picks things ending with z.What would pick things starting with a and ending is s? S: a%s [with confidence in their voices] • L1 looks up, rather than Student • 'wildcard character' technically correct, but did not help student • L2 lay explanation with examples, and question Introduction Method Model Results Conclusions

20. Results: Audio Transcripts • Session 1 (5 conversations) (10m 23s, 2m 34s, 3m 45s, 3m 56s, 26m 3s). • Session 2 (9 conversations) (6m 51s, 1m 44s, 41s, 1m 10s, 1m 33s, 11m 5s, 4m 44s, 3m 8s, 6m 49s). • Session 3 (10 conversations) (3m 6s, 2m 9s, 1m, 11m 27s, 3m 16s, 50s, 1m 2s, 21m 30s, 1m 19s, 5m 28s). • total 24 participants (out of 110) Introduction Method Model Results Conclusions

21. Results: Audio Transcript 1 S: 'but that doesn't work' L: 'OK, when you say "It doesn't work"' S: 'It runs, there are no errors, but there isn't a new record' L: 'OK, right, how can we pause the program and see it internally' S: 'debugger' L: 'Yeah' • Lecturer guiding learning by questioning Introduction Method Model Results Conclusions

22. Conclusions / Literature • Strong History of Similar Approach • Socratic Method(learning by questioning) • Galileo Galilei (1564 - 1642)'You cannot teach a man anything;you can only help him find it within himself' • Student-Centred Learning • Constructivism • Assimilation vs. Accommodation • limited concrete details • how this translates into programming tutorial student-lecturer interactions • new lecturers Introduction Method Model Results Conclusions

23. Further work • Looking for participants Introduction Method Model Results Conclusions

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