Skip to main content
SpringerLink
Log in

Research in Computer Science Education 4

  • Chapter
  • First Online:
Guide to Teaching Computer Science

  • 1466 Accesses

Abstract

Computer science education research refers to different aspects such: students’ difficulties, misconceptions, and cognitive abilities, to vary activities that can be integrated in the learning process, to the advantages of using visualization and animations tools, to the computer science teacher’s role, and more. This meaningful sheered knowledge of the CS education community can enrich the prospective computer science teachers’ perspective. The chapter exposes the MTCS students' to that reach resource, and practice ways in which they can be used in their future work. This knowledge may enhance lesson preparation, kind of activities developed for learners, awareness to learners’ difficulties, ways to improve concept understanding, as well as testing and grading learners’ projects and tests. We first explain the importance of exposing the students to the knowledge gained by the computer science education research community. Then, we demonstrate different issues addressed in such research works and suggest activities to facilitate with respect to this topic.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    See http://portal.acm.org/dl.cfm

  2. 2.

    The 2014 conference website is: http://sigcse2014.sigcse.org/

  3. 3.

    The 2014 conference website is: http://iticse2014.it.uu.se/

  4. 4.

    The 2014 conference website is: http://www.issep2014.org/

  5. 5.

    See http://portal.acm.org/toc.cfm?id=J688

  6. 6.

    See http://portal.acm.org/browse_dl.cfm?linked=1&part=magazine&idx=J1268&coll=portal&dl=ACM&CFID=77578246&CFTOKEN=38064848

  7. 7.

    See http://www.tandf.co.uk/journals/titles/08993408.asp

  8. 8.

    See http://portal.acm.org/browse_dl.cfm?linked=1&part=transaction&idx=J1193&coll=portal&dl=ACM

  9. 9.

    See http://www.wipsce.org/2014/index.php, the 2014 conference website

References

  • Armoni M (2009) Reduction in computer science: a (mostly) quantitative analysis of reductive solutions to algorithmic problems. JERIC 8(4):1–30

    Article  Google Scholar 

  • Baloian N, Luther W, Sánchez J (2002) Modeling educational software for people with disabilities: theory and practice. Proceedings of the 5th International ACM Conference on Assistive Technologies, pp 111–118

    Google Scholar 

  • Ben-Bassat Levy R, Ben-Ari M (2007). We work so hard and they don't use it: acceptance of software tools by teachers. In Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (ITiCSE ’07). ACM, New York, USA, pp 246–250

    Google Scholar 

  • Ben-Bassat Levy R, Ben-Ari M (2008). Perceived behavior control and its influence on the adoption of software tools. SIGCSE Bull 40(3):169–173

    Article  Google Scholar 

  • Ben-Bassat Levy R, Ben-Ari M, Uronen PA (2003) The jeliot 2000 program animation system. Comput Educ 40(1):1–15

    Article  Google Scholar 

  • Blum L, Cortina TJ (2007) CS4HS: An outreach program for high school CS teachers. ACM SIGCSE Bull 39(1):19–23

    Article  Google Scholar 

  • Brandes O, Vilner T, Zur E (2010) Software design course for leading CS in-service teachers. Proceedings of ISSEP, Lecture Notes in Computer Science, vol 5941, 49–60

    Google Scholar 

  • Bunde DP, Graf M, Han D, Mache J (2014). Parallel programming paradigms illustrated (abstract only). In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14). ACM, New York, USA, pp 722–722

    Google Scholar 

  • Chaffin A, Doran K, Hicks D et al (2009) Experimental evaluation of teaching recursion in a video game. Proceedings of the 2009 ACM SIGGRAPH Symposium on Video, pp 79–86

    Google Scholar 

  • Cross J, Hendrix D, Barowski L, Umphress D (2014) Dynamic program visualizations: an experience report. In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14). ACM, New York, USA, pp 609–614

    Google Scholar 

  • Dark MJ, Winstead J (2005) Using educational theory and moral psychology to inform the teaching of ethics in computing. Proceedings InfoSecCD, pp 27–31

    Google Scholar 

  • Denier S, Sahraoui H (2009) Understanding the use of inheritance with visual patterns. Proceedings of the 3rd International Symposium on Empirical Software Engineering and Measurement, pp 79–88

    Google Scholar 

  • de Raadt M (2007) A review of Australasian investigations into problem solving and the novice programmer. Comput Sci Educ 17(3):201–213

    Article  Google Scholar 

  • de Raadt M, Toleman M, Watson R (2004) Training strategic problem solvers. ACM SIGCSE Bull 36(2):48–51

    Article  Google Scholar 

  • Edwards SH (2003) Rethinking computer science education from a test-first perspective. 18th Annual ACM SIGPLAN OOPSLA Conference, pp 148–155

    Google Scholar 

  • Erlwanger SH (1973) Benny’s conception of rules and answers in IPI mathematics. JCMB 1(2):7–26

    Google Scholar 

  • Fleck A (2007) Prolog as the first programming language. ACM SIGCSE Bull 39(4):61–64

    Article  Google Scholar 

  • Fluery AN (1993). Student beliefs about Pascal programming. J Educ Comput Res 9(3): 355–371

    Article  Google Scholar 

  • Forišek M, Steinová M (2010) Didactic games for teaching information theory. In: Vahrenhold J (ed) Lecture notes computer science, vol 5941. Springer, Berlin, pp 86–99

    Google Scholar 

  • Gal-Ezer J, Harel D (1998) What (else) should CS educators know?. Communic ACM 41(9):77–84

    Article  Google Scholar 

  • Gal-Ezer J, Zur E (2013) What (else) should CS Educators Know?—Revisited, WiPSCE ’13, Aarhus, Denmark, pp 84–87

    Google Scholar 

  • Garner S, Haden P, Robins A (2005) My program is correct but it doesn’t run: A preliminary investigation of novice programmers’ problems. Proceedings of the 7th Australasian Conference on Computing Education, vol 42, pp 173–180 (Young A, Tolhurst D (eds))

    Google Scholar 

  • Haberman B, Ragonis N (2010) So different though so similar?—Or vice versa? Exploration of the logic programming and the object-oriented programming paradigms. Iss Informing Sci Inf Technol 7:393–402

    Google Scholar 

  • Hanks B (2008) Problems encountered by novice pair programmers. JERIC 7(4):1–13

    Article  Google Scholar 

  • Hauer A, Daniels M (2008) A learning theory perspective on running open ended group projects (OEGPs). Proceedings 10th Conference on Australasian Computing Education, vol 78, pp 85–91 (Australian Compu. Soc., Darlinghurst, Australia)

    Google Scholar 

  • Hazzan O, Har-Shai G (2013) Teaching computer science soft skills as soft concepts. In Proceeding of the 44th ACM technical symposium on Computer science education (SIGCSE ’13). ACM, New York, USA, pp 59–64

    Google Scholar 

  • Hazzan O, Har-Shai G (2014) Teaching and learning computer science soft skills using soft skills: the students’ perspective. In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14). ACM, New York, USA, pp 567–572

    Google Scholar 

  • Joni, S.A., Soloway, E. (1986). But my program runs! Discourse rules for novice programmers. J Educ Comput Res 2(1):95–128

    Article  Google Scholar 

  • Kaczmarczyk LC, Petrick ER, East JP et al (2010) Identifying student misconceptions of programming. Proceedings 41st ACM Technical Symposium on Computer Science Education. pp 107–111

    Google Scholar 

  • Karpierz K, Wolfman SA (2014) Misconceptions and concept inventory questions for binary search trees and hash tables. In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14). ACM, New York, USA, pp 109–114

    Google Scholar 

  • Kölling M, Quig B, Patterson A et al (2003) The BlueJ system and its pedagogy. Comput Sci Educ 13(4):249–268

    Article  Google Scholar 

  • Krauskopf K, Zahn C, Hesse FW (2012) Leveraging the affordances of youtube: the role of pedagogical knowledge and mental models of technology functions for lesson planning with technology. Comput Educ 58(4):1194–1206

    Article  Google Scholar 

  • Lapidot T, Ragonis N (2013) Supporting high school computer science teachers in writing academic papers. In Proceedings of the 18th ACM conference on Innovation and technology in computer science education (ITiCSE ’13). ACM, New York, USA, pp 325–325

    Google Scholar 

  • Lee YL (2011) The development of technological pedagogical content knowledge for science learning with a three-dimensional interactive computer simulation. Ph. D. Dissertation, University of Washington, Seattle, WA, USA Advisors Mark Windschitl AAI3472171

    Google Scholar 

  • Ioannou I, Angeli C (2013) Teaching computer science in secondary education: a technological pedagogical content knowledge perspective. In Proceedings of the 8th Workshop in Primary and Secondary Computing Education (WiPSE ’13). ACM, New York, USA, pp 1–7

    Google Scholar 

  • McCauleya R, Fitzgeraldb S, Lewandowskic G et al (2008) Debugging: a review of the literature from an educational perspective. Comput Sci Educ 18(2):67–92

    Article  Google Scholar 

  • Miller B (2007) Exploring python as a learning and teaching language. J Comput Small Coll 22(3):262–263

    Google Scholar 

  • Miller D, Soh LK, Chiriacescu V, Ingraham E, Shell DF, Hazley MP (2014) Integrating computational and creative thinking to improve learning and performance in CS1. In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14). ACM, New York, USA, pp 475–480

    Google Scholar 

  • Mittermeir RT, Bischof E, Hodnigg K (2010) Showing core-concepts of informatics to kids and their teachers. In: Vahrenhold J (ed) Lecture notes in Computer Science, vol 5941. Springer, Berlin, pp 143–154

    Google Scholar 

  • Moritz SH, Blank GD (2005) A design-first curriculum for teaching Java in a CS1 course. ACM SIGCSE Bull 37(2):89–93

    Article  Google Scholar 

  • Mouza C, Karchmer-Klein R, Nandakumar R, Ozden SY, Hu L (2014) Investigating the impact of an integrated approach to the development of preservice teachers’ technological pedagogical content knowledge (TPACK). Comput Educ 71:206–221

    Article  Google Scholar 

  • Murphy L, Lewandowski G, McCauley R et al (2008) Debugging: the good, the bad, and the quirky: a qualitative analysis of novices’ strategies. Proceedings 39th SIGCSE Technical Symposium Computer Science Education, pp 163–167

    Google Scholar 

  • Ni L (2009) What makes CS teachers change? Factors influencing CS teachers’ adoption of curriculum innovations. Proceedings 40th ACM Technical Symposium Computer Science Education, pp 544–548

    Google Scholar 

  • Paul O, Vahrenhold J (2013) Hunting high and low: instruments to detect misconceptions related to algorithms and data structures. In Proceeding of the 44th ACM technical symposium on Computer science education (SIGCSE ’13). ACM, New York, USA, pp 29–34

    Google Scholar 

  • Pea, R.D. (1986). Language-independent conceptual “bugs” in novice programming. J Educ Comput Res 2(1):25–36

    Article  Google Scholar 

  • Perkins DN, Martin F (1986) Fragile knowledge and neglected strategies in novice programmers. In: Soloway E, Iyengar S (eds) Empirical studies of programmers. Ablex Pub, Norwood, pp 213–229

    Google Scholar 

  • Ragonis N (2010) A pedagogical approach to discussing fundamental object-oriented programming principles using the ADT SET. ACM Inroads 1(2):42–52

    Article  Google Scholar 

  • Ragonis N, Ben-Ari M (2005) On understanding the statics and dynamics of object-oriented programs. SIGCSE Bull 37(1):226–230

    Article  Google Scholar 

  • Ragonis N, Hazzan O (2015, in review) What Are Computer Science Educators Interested In? The CASE of SIGCSE Conferences. Submitted to SIGCSE

    Google Scholar 

  • Resnick M, Maloney J, Monroy-Hernández A et al (2009) Scratch: programming for all. Commun ACM 52(11):60–67

    Article  Google Scholar 

  • Rodger SH, Bashford M, Dyck L et al (2010) Enhancing K-12 education with Alice programming adventures. Proceedings on Innovation and Technology in Computer Science Education, pp 234–238

    Google Scholar 

  • SamurÇay, R. (1985). Learning programming: an analysis of looping strategies used by beginning students. For Learn Math 5(1):37–43

    Google Scholar 

  • Samurçay R (1989) The concept of variable in programming: its meaning and use in problem-solving by novice programmers. In: Soloway E, Spohrer JC (eds) Studying the novice programmer. Lawrence Erlbaum Associates, New Jersey, pp 161–178

    Google Scholar 

  • Shulman LS (1986) Those who understand: knowledge growth in teaching. J Educ Teach 15(2):4–14

    Google Scholar 

  • Shulman LS (1990) Reconnecting foundations to the substance of teacher education. Teach Coll Record 91(3):300–310

    Google Scholar 

  • Simon B, Parris J, Spacco J (2013) How we teach impacts student learning: peer instruction vs. lecture in CS0. In Proceeding of the 44th ACM technical symposium on Computer science education (SIGCSE ’13)

    Google Scholar 

  • Smith JP III, diSessa AA, Roschelle J (1993) Misconceptions reconceived: a constructivist analysis of knowledge in transition. J Learn Sci 3(2):115–163

    Article  Google Scholar 

  • Soh L, Samal A, Nugent G (2005) A framework for CS1 closed laboratories. JERIC 5(4):2

    Article  Google Scholar 

  • Spohrer, J.C., Soloway, E. (1986). Analyzing the high frequency bugs in novice programs. In Soloway E, Iyengar S (eds). Empirical studies of programmers. Ablex Pub.: Norwood, pp 230–251

    Google Scholar 

  • Stolin Y, Hazzan O (2007) Students’ understanding of computer science soft ideas: the case of programming paradigm. ACM SIGCSE Bull 39(2):65–69

    Article  Google Scholar 

  • Tashakkori RM, Parry RM, Benoit A, Cooper RA, Jenkins JL, Westveer NT (2014) Research experience for teachers: data analysis & mining, visualization, and image processing. In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14). ACM, New York, USA, pp 193–198

    Google Scholar 

  • Van Roy PA, Flatt M et al (2003) The role of language paradigms in teaching programming. Proceedings of the 34th SIGCSE Technical Symposium Computer Science Education, pp 269–270

    Google Scholar 

  • Voyles MM, Haller SM, Fossum TV (2007) Teacher responses to student gender differences. Proceedings of the 12th Annual SIGCSE Conference on Innovation & Technology in Computer Science Education, pp 226–230

    Google Scholar 

  • Watson C, Li FWB, Godwin JL (2014). No tests required: comparing traditional and dynamic predictors of programming success. In Proceedings of the 45th ACM technical symposium on Computer science education (SIGCSE ’14)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. Education in Science & Technology, Technion—Israel Institute of Technology, Technion City, Haifa, Israel

    Orit Hazzan & Tami Lapidot

  2. Computer Science Studies, Faculty of Education, Beit Berl College, Doar Beit Berl, Israel

    Noa Ragonis

  3. Dept. Education in Science & Technology, Technion—Israel Institute of Technology, Doar Beit Berl, Israel

    Noa Ragonis

Authors
  1. Orit Hazzan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tami Lapidot
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Noa Ragonis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Orit Hazzan .

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag London Limited

About this chapter

Cite this chapter

Hazzan, O., Lapidot, T., Ragonis, N. (2014). Research in Computer Science Education 4. In: Guide to Teaching Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-6630-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-6630-6_4

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6629-0

  • Online ISBN: 978-1-4471-6630-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation