Digital Competency and Digital Literacy is at Stake
Author(s):
Maria Csernoch (presenting / submitting) Piroska Biró
Conference:
ECER 2014
Format:
Paper

Session Information

16 SES 02 B, Digital Literacy and Learning Styles

Paper Session

Time:
2014-09-02
15:15-16:45
Room:
B008 Anfiteatro
Chair:
Colin Harrison

Contribution

Digital competency (Lankshear & Knobel, 2008) and digital literacy (Glister, 1997; Lankshear & Knobel, 2008) have been among the most popular expressions in the curricula of recent years, and the effect of both on different generations – the Y and Z generations of the digital natives (the bit-generations) and the X generation of digital immigrants (Dani, 2013; Jukes, McCain & Crockett, 2010) – is one of society's main concerns. We will give some consideration to these newly emerged expressions and some background information related to them. First of all, the most important point is to emphasize that in order to develop digital competency effectively and efficiently and to achieve a satisfactory level in digital literacy, formal education is needed. For formal education, teachers are needed. For teachers, teacher education is needed. At this point the loop is closed, and we are facing the chicken and the egg problem: who teaches the teachers if there are no teachers? In Computer Sciences/Informatics Education (CSI) this is one of the most crucial questions and for an answer we have to look back in time to the emergence of the subject. The contradictions, both of the science itself, and of the developing commercialized world as it interacted with the science, affect teachers, teacher education and consequently the development of digital competency and literacy.

Recent studies have proved that more than 90% of the e-documents carry errors, and uneducated computer users cause serious financial losses by providing unreliable data and by using up much more time than problems require (Panko & Aurigemma, 2010; van Deursen & van Dijk, 2012), while other publications have provided evidence that these mistakes are due to a lack of algorithmic skills and thinking (Biró & Csernoch, 2013a, 2013b). However, the Students On Line session of the PISA 2009 survey proved that computer usage in schools does not necessarily increase the level of digital competence (OECD, 2011). This ambiguity clearly indicates that we have serious problems with the methods employed to teach CSI.

The problems of CSI education emerge from the particularities and the contradictions of the science: (1) a new science without any direct predecessors, (2) a science developing at a speed previously unknown in any other science, (3) the commercialized word developing around the science, and (4) the pressures and the needs for computer usage and for information.

The pioneer teachers were self-educated, in most cases not supervised, and if so, certainly not by experts in the didactics of the subject, because they did not exist. These first teachers taught mainly programming languages, algorithms, binary arithmetic, and computer architecture. Over time they became accepted, whether they were qualified or not; they used methods they developed themselves, without proving their efficiency and effectiveness, due to a lack of time and methods.

In the meantime computer science developed at an incredible speed, and the new graphical user interfaces (GUI) using the mouse increased the number of users and changed the approach and attitude towards computers. Everyone started to use computers regardless of any background knowledge, and software developers encouraged them to do so. These companies claimed that by using the GUI and its accompanying wizards the users would be able to solve problems. Users need do nothing else but click here and there and they will find the solution.

Even teachers fell for this, and, giving up the teaching of algorithms, switched to aimless clicking, not looking for the algorithms in these new programs; consequently they stopped developing their own and the students’ algorithmic skills.

Method

Fiasco Nowadays it has been proved that most of the computer related activities are metacognitive processes (Biró & Csernoch, 2013a), because users are supposed to read and understand the signs and messages of the GUI and the wizards, and they must make their decisions on the basis of the information offered. However, in most cases users adopt trial-and-error driven solutions (TAEW, Trial-and-error wizard-based) (Csernoch & Biró, 2014), mainly because they do not understand and are not interested in the messages provided by the software. Consequently, these methods of creating e-documents can be categorized as surface approach methods, and such as they are not sufficient for problem solving. Several other consequences of the teachers’ choice of the TAEW-approach could be reported, but we must emphasize one, which has far-reaching consequences: the method is not suitable for measuring the students' knowledge (Csernoch & Biró, 2013b). Tests of students and teachers of Informatics in Hungary have revealed that the teachers hardly know any more than the students, and more disconcertingly, they are not able to judge the students’ knowledge (Csernoch & Biró, 2013b). Solutions To solve the problems of the digital world algorithms have to be built and these algorithms have to be coded. The methods which support this approach are entitled Computer-algorithmic and debugging-based methods (CAAD) (Csernoch & Biró, 2014, 2013a, 2013b), and belong to the deep-approach metacognitive processes (Case & Gunstone, 2002, 2003; Case, Gunstone & Lewis, 2001). The CAAD approach can be applied to any computer related problems. We have developed and tested CAAD-based methods for solving spreadsheet (Csernoch, 2012; Csernoch & Biró 2014) and word-processing problems (Csernoch, 2009). In both cases the primary aims of the methods are that in advance of the actualization of the problem the algorithms have to be created, and based on the algorithm the coding process follows (Biró & Csernoch, 2013a, 2013b). In spreadsheet, since it is classed as a functional language the coding process is more closely related to other programming languages, while in word-processing the coding is carried out by clicking on the commands, which usually appear in the form of buttons, in the planned order. The core of our CAAD-based methods, both in spreadsheet and word-processing, is based on Nielsen’s minimalist theory (Nielsen, 1993) and our results by testing the students’ knowledge (Csernoch & Biró 2013b).

Expected Outcomes

With spreadsheet we claim that at the beginning we have to teach as simple and as low number of functions as possible, and based on these functions we have to teach how to build multilevel formulas. The level of formulas and the number of functions can be increased continuously as the students develop. The other advantage of the method is that debugging has now become available. With word-processing the CAAD-based method is built around the definition of properly formatted text, which says that a text is properly formatted if it is invariant to changes (Csernoch, 2009). This means that changes to the text are allowed, but without any retyping or reformatting beyond the intentions of the user. Along with this definition we have to provide tools for the actualization, i.e. the coding of the problems: (1) the different groups of errors have to be defined for easier recognition and in order to avoid them, and (2) the scope of the commands must be defined as well. Equipped with these tools the process of creating a text can be planned in advance, and there is no need for a randomly carried out sequences of clicks. In general, we claim that digital literacy is not a sequence of uncontrollable TEAW-activities. Instead, as we have proved by applying our CAAD-based methods in spreadsheet and word-processing and by testing our students and teachers, these methods are more promising than the commercialized surface-approach methods (Csernoch & Biró, 2013b). Beyond the direct advantages of building algorithms to solve problems and create error-free documents in computer applications, through the deep-approach methods, these applications would serve as introductory languages to high level programming languages, as predicted, but not proved, by Nielsen in 1993.

References

Biró, P. & Csernoch, M. (2013a). Deep and surface structural metacognitive abilities of the first year students of Informatics. 4th IEEE International Conference on Cognitive Infocommunications, Proceedings, Budapest, 521–526. Biró, P. & Csernoch, M. (2013b). Programing skills of the first year students of Informatics. Elsőéves informatikushallgatók algoritmizáló készségei. XXIII. SzámOkt, EMT, Nagyszeben. 154–159. Case, J. & Gunstone, R. (2002). Metacognitive development as a shift in approach to learning: an in-depth study. Studies in Higher Education, 27(4), 459–470. Case, J. & Gunstone, R. (2003). Approaches to learning in a second year chemical engineering course. International Journal of Science Education, 25(7), 801–819. Case, J., Gunstone R. & Lewis A. (2001). Students' metacognitive development in an innovative second year chemical engineering course, Research in Science Education, 31(3), pp. 331–355. Csernoch, M. (2009). Teaching word processing – the theory behind. Teaching Mathematics and Computer Science. 2009/1. pp. 119–137. Csernoch, M. (2012). Introducing Conditional Array Formulas in Spreadsheet Classes. EDULEARN12 Proceedings. Barcelona, Spain. Publisher: IATED, 7270–7279. Csernoch, M. & Biró, P. (2013a). Teachers’ Assessment and Students’ Self-Assessment on The Students’ Spreadsheet Knowledge. EDULEARN13 Proceedings July 1st-3rd, 2013 — Barcelona, Spain. Publisher: IATED. pp. 949–956. Csernoch, M. & Biró, P. (2013b). Spreadsheet misconceptions, spreadsheet errors. Hungarian Conference on Educational Research, Debrecen. Csernoch, M. & Biró, P. (2014). Spreadsheet misconception, spreadsheet errors. Oktatáskutatás határon innen és túl. HERA Évkönyvek I., ed. Juhász Erika, Kozma Tamás, Publisher: Belvedere Meridionale, Szeged, pp. 370-395. Dani, E. (2013). Bit-Generations and the Digital Environment. in Current Issues In Some Disciplines, Karlovitz János Tibor (ed). Jukes, I., McCain T. & Crockett, L. (2010). Understanding the Digital Generation: Teaching and Learning in the New Digital Landscape. 21st Century Fluency Project Inc. ISBN-13: 978-1412938440. OECD (2011). PISA 2009 Results: Students on Line: Digital Technologies and Performance (Vol. VI). http://dx.doi.org/10.1787/9789264112995-en. http://browse.oecdbookshop.org/oecd/pdfs/free/9811031e.pdf. Retrieved: 02.01.2014. Glister, P. (1997). Digital Literacy. John Wiley & Sons, Inc. Lankshear, C. & Knobel, M. (2008). Digital Literacies: Concepts, Policies and Practices. New York: Peter Lang. https://www.academia.edu/3011380/Digital_literacy_and_participation_in_online_social_networking_spaces. Retrieved: 02.01.2014. Nielsen, J. (1993). Usability Engineering, Academic Press, Boston, MA. Panko, R. & Aurigemma S. (2010). Revising the Panko-Halverson taxonomy of spreadsheet errors. Decis. Support Syst. 49, 2: 235–244. van Deursen A. & van Dijk J. (2012). CTRL ALT DELETE. Lost productivity due to IT problems and inadequate computer skills in the workplace. Enschede: Universiteit Twente.http://www.ecdl.org/media/ControlAltDelete_LostProductivityLackofICTSkills_UniverstiyofTwente1.pdf. Retrieved: 02.01.2014.

Author Information

Maria Csernoch (presenting / submitting)
University of Debrecen Faculty of Informatics
Debrecen
University of Debrecen Faculty of Informatics, Hungary

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