Page 12 - Fister jr., Iztok, Andrej Brodnik, Matjaž Krnc and Iztok Fister (eds.). StuCoSReC. Proceedings of the 2019 6th Student Computer Science Research Conference. Koper: University of Primorska Press, 2019
P. 12
CONCLUSIONS study of assessment of programming skills of first-year
cs students. volume 33, pages 125–180, USA, 2001.
The result of this work is a framework proposal for CT in ACM New York.
introductory programming in higher education. The fra-
mework provides a useful starting point for further research. [12] S. Papert. Mindstorms: children, computers, and
The future work should be oriented toward implementing powerful ideas. Basic Books, Inc, USA, 1980.
computer programming artefact based on proposed CTF.
The envisioned outcome of further research might be the [13] D. Parnas. On the criteria to be used in decomposing
CT instrument suited for implicitly assessing CT based on systems into modules. volume 15, pages 1053–1058,
computer programming tasks within the higher education USA, 1972. ACM.
level.
[14] M. S. Peteranetz, L.-K. Soh, and E. Ingraham.
Furthermore, the proposed CTF should stimulate further Building computational creativity in an online course
research in the context of success or failure of novices in in- for non-majors. pages 442–448, Minneapolis, USA,
troductory programming in higher education, often referred 2019. ACM New York.
as “CS1 dropout rate”. The researchers observed that the
dropout rate problem can be divided to the following two [15] G. Rambally. Integrating computational thinking in
categories: language problem and design problem [11]. If discrete structures. pages 99–119, Switzerland, 2017.
these categories could be mapped into the computational Springer International Publishing AG.
thinking context, then the proposed CTF could serve as a
foundation for CT assessment, a potential predictor for the [16] M. Romero, A. Lepage, and B. Lille. Computational
CS1 dropout rate. thinking development through creative programming
in higher education. volume 14, pages 1–15, 2017.
6. REFERENCES
[17] M. Sahami, A. Danyluk, S. Fincher, and K. Fisher.
[1] E. Billionniere. Assessing Cognitive Learning of Computer Science Curricula 2013. The Joint Task
Analytical Problem Solving. Doctoral dissertation, Force on Computing Curricula Association for
Arizona State University, December 2011. Computing Machinery (ACM) IEEE Computer
Society, USA, December 2013.
[2] D. Bjørner. Software Engineering 3 - Domains,
Requirements, and Software Design. Springer-Verlag, [18] C. Selby and J. Woollard. Refining an understanding
Heidelberg, 2006. of computational thinking. University of Southampton
Institutional Repository, 2014.
[3] K. Brennan and M. Resnick. New frameworks for
studying and assessing the development of [19] I. Shaw, J. Greene, and M. Mark. The SAGE
computational thinking. pages 1–25, Vancouver, BC, Handbook of Evaluation. SAGE Publications Ltd,
Canada, 2012. USA, 2013.
[4] B. Bubnic and T. Kosar. Towards a consensus about [20] L. Smith and J. Cordova. Weighted primary trait
computational thinking skills: Identifying agreed analysis for computer program evaluation. pages
relevant dimensions. Newcastle, UK, 2019. 14–19. Consortium for Computing Sciences in
Proceedings of the 30th Annual Workshop of the Colleges, 2005.
Psychology of Programming Interest Group - PPIG
2019 - submited for publication. [21] K. Y. Tang, T. L. Chou, and C. C. Tsai. A content
analysis of computational thinking research: An
[5] K. Czarnecki. Generative Programming: Methods, international publication trends and research typology.
Tools, and Applications. Addison-Wesley Professional; pages 1–11, USA, 2019. Springer Nature.
1 edition, June 2000.
[22] M. Tedre. The long quest for computational thinking.
[6] P. Donaldson and Q. Cutts. Flexible low-cost activities pages 120–129. Koli, Finland, Koli Calling ’16
to develop novice code comprehension skills in schools. Proceedings of the 16th Koli Calling International
pages 1–4, Potsdam, Germany, 2018. ACM New York. Conference on Computing Education Research,
November 2016.
[7] L. Gouws, K. Bradshaw, and P. Wentworth. First year
student performance in a test for computational [23] A. E. Tew. Assessing Fundamental Introductory
thinking. pages 271–277, East London, South Africa, Computing Concept Knowledge in a Language
2013. ACM New York. Independent Manner. Doctoral dissertation, Georgia
Institute of Technology, December 2010.
[8] D. Knuth. The Art of Computer Programming:
Volume 1: Fundamental Algorithms, Third Edition. [24] D. Weintrop, E. Beheshti, and M. Horn. Defining
Addison-Wesley, USA, 1997. computational thinking for mathematics and science
classrooms. volume 25, pages 127–147, February 2016.
[9] A. J. Ko, R. Abraham, L. Beckwith, A. Blackwell, and
M. Burnett. The state of the art in end-user software [25] J. Wing. Computational thinking. volume 49, pages
engineering. volume 43, USA, April 2011. ACM New 33–35, USA, March 2006. ACM New York.
York.
[26] A. Zeller. Why Programs Fail: A Guide to Systematic
[10] A. Luxton-Reilly, B. A. Becker, Y. Cao, and Debugging 2nd Edition. Morgan Kaufmann, USA,
R. McDermott. Developing assessments to determine June 2009.
mastery of programming fundamentals. pages 47–69,
July 2017.
[11] M. McCracken, V. Almstrum, D. Diaz, and
M. Guzdial. A multi-national, multi-institutional
StuCoSReC Proceedings of the 2019 6th Student Computer Science Research Conference 12
Koper, Slovenia, 10 October
cs students. volume 33, pages 125–180, USA, 2001.
The result of this work is a framework proposal for CT in ACM New York.
introductory programming in higher education. The fra-
mework provides a useful starting point for further research. [12] S. Papert. Mindstorms: children, computers, and
The future work should be oriented toward implementing powerful ideas. Basic Books, Inc, USA, 1980.
computer programming artefact based on proposed CTF.
The envisioned outcome of further research might be the [13] D. Parnas. On the criteria to be used in decomposing
CT instrument suited for implicitly assessing CT based on systems into modules. volume 15, pages 1053–1058,
computer programming tasks within the higher education USA, 1972. ACM.
level.
[14] M. S. Peteranetz, L.-K. Soh, and E. Ingraham.
Furthermore, the proposed CTF should stimulate further Building computational creativity in an online course
research in the context of success or failure of novices in in- for non-majors. pages 442–448, Minneapolis, USA,
troductory programming in higher education, often referred 2019. ACM New York.
as “CS1 dropout rate”. The researchers observed that the
dropout rate problem can be divided to the following two [15] G. Rambally. Integrating computational thinking in
categories: language problem and design problem [11]. If discrete structures. pages 99–119, Switzerland, 2017.
these categories could be mapped into the computational Springer International Publishing AG.
thinking context, then the proposed CTF could serve as a
foundation for CT assessment, a potential predictor for the [16] M. Romero, A. Lepage, and B. Lille. Computational
CS1 dropout rate. thinking development through creative programming
in higher education. volume 14, pages 1–15, 2017.
6. REFERENCES
[17] M. Sahami, A. Danyluk, S. Fincher, and K. Fisher.
[1] E. Billionniere. Assessing Cognitive Learning of Computer Science Curricula 2013. The Joint Task
Analytical Problem Solving. Doctoral dissertation, Force on Computing Curricula Association for
Arizona State University, December 2011. Computing Machinery (ACM) IEEE Computer
Society, USA, December 2013.
[2] D. Bjørner. Software Engineering 3 - Domains,
Requirements, and Software Design. Springer-Verlag, [18] C. Selby and J. Woollard. Refining an understanding
Heidelberg, 2006. of computational thinking. University of Southampton
Institutional Repository, 2014.
[3] K. Brennan and M. Resnick. New frameworks for
studying and assessing the development of [19] I. Shaw, J. Greene, and M. Mark. The SAGE
computational thinking. pages 1–25, Vancouver, BC, Handbook of Evaluation. SAGE Publications Ltd,
Canada, 2012. USA, 2013.
[4] B. Bubnic and T. Kosar. Towards a consensus about [20] L. Smith and J. Cordova. Weighted primary trait
computational thinking skills: Identifying agreed analysis for computer program evaluation. pages
relevant dimensions. Newcastle, UK, 2019. 14–19. Consortium for Computing Sciences in
Proceedings of the 30th Annual Workshop of the Colleges, 2005.
Psychology of Programming Interest Group - PPIG
2019 - submited for publication. [21] K. Y. Tang, T. L. Chou, and C. C. Tsai. A content
analysis of computational thinking research: An
[5] K. Czarnecki. Generative Programming: Methods, international publication trends and research typology.
Tools, and Applications. Addison-Wesley Professional; pages 1–11, USA, 2019. Springer Nature.
1 edition, June 2000.
[22] M. Tedre. The long quest for computational thinking.
[6] P. Donaldson and Q. Cutts. Flexible low-cost activities pages 120–129. Koli, Finland, Koli Calling ’16
to develop novice code comprehension skills in schools. Proceedings of the 16th Koli Calling International
pages 1–4, Potsdam, Germany, 2018. ACM New York. Conference on Computing Education Research,
November 2016.
[7] L. Gouws, K. Bradshaw, and P. Wentworth. First year
student performance in a test for computational [23] A. E. Tew. Assessing Fundamental Introductory
thinking. pages 271–277, East London, South Africa, Computing Concept Knowledge in a Language
2013. ACM New York. Independent Manner. Doctoral dissertation, Georgia
Institute of Technology, December 2010.
[8] D. Knuth. The Art of Computer Programming:
Volume 1: Fundamental Algorithms, Third Edition. [24] D. Weintrop, E. Beheshti, and M. Horn. Defining
Addison-Wesley, USA, 1997. computational thinking for mathematics and science
classrooms. volume 25, pages 127–147, February 2016.
[9] A. J. Ko, R. Abraham, L. Beckwith, A. Blackwell, and
M. Burnett. The state of the art in end-user software [25] J. Wing. Computational thinking. volume 49, pages
engineering. volume 43, USA, April 2011. ACM New 33–35, USA, March 2006. ACM New York.
York.
[26] A. Zeller. Why Programs Fail: A Guide to Systematic
[10] A. Luxton-Reilly, B. A. Becker, Y. Cao, and Debugging 2nd Edition. Morgan Kaufmann, USA,
R. McDermott. Developing assessments to determine June 2009.
mastery of programming fundamentals. pages 47–69,
July 2017.
[11] M. McCracken, V. Almstrum, D. Diaz, and
M. Guzdial. A multi-national, multi-institutional
StuCoSReC Proceedings of the 2019 6th Student Computer Science Research Conference 12
Koper, Slovenia, 10 October
