Abstract
The paper addresses the increased need for data literacy education in higher education. The background for this is provided by the international Erasmus+ project DaLiCo, in which four universities of applied sciences are developing concepts for the fostering of data literacy. Research results and lessons learned from project activities such as the joint summer school will be presented.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Heidrich, J., Bauer, P., Krupka, D.: Future Skills: Ansätze zur Vermittlung von Data Literacy in der Hochschulbildung. Arbeitspapier Nr. 37. Hochschulforum Digitalisierung, Berlin (2018)
Grillenberger, A.: Von Datenmanagement zu Data Literacy: Informatikdidaktische Aufarbeitung des Gegenstandsbereichs Daten für den allgemeinbildenden Schulunterricht. FU Berlin, Berlin (2018)
Gulsen, G.: Data Literacy from Theory to Reality: How Does it Look? Vrije Universiteit Brussel, Brüssel (2019)
Koltay, T.: Data literacy for researchers and data librarians. J. Librariansh. Inf. Sci. 49(1), 3–14 (2017)
Ridsdale, C., et al.: Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report (2015)
Bowker, G.C., Star, S.L.: Sorting Things Out: Classification and its Consequences. MIT press, Cambridge, MA (2009)
Schüller, K.: Future Skills: a Framework for Data Literacy – Competence Framework and Research Report. Working Paper Nr 53. Hochschulforum Digitalisierung, Berlin (2020)
Data-Pop Alliance: Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data. Data-Pop Alliance White Paper Series. Data-Pop Alliance (2015)
School of Data (2021). https://schoolofdata.org/
Stifterverband (2021). https://www.stifterverband.org/data-literacy-education#netzwerk
Schüller, K., Busch, P., Hindinger, C.: Future Skills: Ein Framework für Data Literacy – Kompetenzrahmen und Forschungsbericht. Hochschulformum Digitalisierung (2019)
Gray, J., Gerlitz, C., Bounegru, L.: Data infrastructure literacy. Big Data Soc. 5(2), 1–13 (2018)
Markham, A.N.: Taking data literacy to the streets: critical pedagogy in the public sphere. Qual. Inq. 26(2), 754–760 (2020)
Tygel, A.F., Kirsch, R.: Contributions of Paulo Freire to a critical data literacy: a populareducation approach. J. Community Informatics 12(3), 108–121 (2016)
D’Ignazio, C., Klein, L.F.: Data Feminism. Mit Press, Cambridge, MA (2020)
Kultusministerkonferenz: Qualifikationsrahmen für deutsche Hochschulabschlüsse (HQR) (2017)
Lokhoff, J., et al.: CoRe—A Tuning Guide to Formulating Degree Programme Profiles Including Programme Competences and Programme Learning Outcomes. Bilbao, Groningen and The Hague (2010)
Carlson, J., Johnston, L., Westra, B., Nichols, M.: Developing an aapproach for data management education: a report from the data information literacy project. Int. J. Digital Curation 8(1), 204–217 (2013)
Prado, J.C., Marzal, M.A.: Incorporating data literacy into information literacy programs: core competencies and contents. Libri 63(2), 123–134 (2013)
Pedersen, A.Y., Caviglia, F.: Data literacy as a compound competence. In: Antipova, T., Rocha, A. (eds.) DSIC18 2018. AISC, vol. 850, pp. 166–173. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-02351-5_21
Giese, T. G., Wende, M., Bulut, S., Anderl, R.: Introduction of data literacy in the undergraduate engineering curriculum. In: Paper Presented at the IEEE Global Engineering Education Conference, EDUCON (2020)
Gläser, C.: Wer spricht die Sprache der Daten? Data literacy in der Lehre am Department Information. API Magazin 1(2), 1–8 (2020)
Jiang, J., Paivarinta, T., Chen, H., Tan, W.: Using learning diary and peer-assessment as afl tools: case study of a sino-finnish collaborative program course. In: 5th International Conference on Education and Social Development (ICESD 2020), pp. 489–493 (2020)
Mayring, P., Fenzl, T.: Qualitative Inhaltsanalyse. In: Baur, N., Blasius, J. (eds.) Handbuch Methoden der empirischen Sozialforschung, pp. 543–556. Springer, Wiesbaden (2014). https://doi.org/10.1007/978-3-531-18939-0_38
Bloom, B.S., Engelhart, M.D., Furst, E.J., Hill, W.H., Krathwohl, D.R.: Taxonomy of Educational Objectives: the Classification of Educational Goals. David McKay Company, New York (1956)
Helliwell, J. F., Layard, R., Sachs, J., De Neve, J. (eds): World Happiness Report. New York (2020)
Koch, C., Wilson, G.: Software Carpentry: Instructor Training. Version 2016. 06, May 2016. https://github.com/carpentries/instructor-training (2016) https://doi.org/10.5281/zenodo.57571
Mepham, B.: A framework for the ethical analysis of novel foods. The ethical matrix. J. Agric. Environ. Ethics 12(2), 165–176 (2000)
Biernacka, K., et al.: Train-the-Trainer Concept on Research Data Management. Berlin (2018)
Osterwalder, A., Pigneur, Y., Clark, T.: Business Model Generation: a Handbook for Visionaries, Game Changers, and Challengers. John Wiley & Sons, Hoboken, NJ (2010)
OpenPM Canvas (2021). https://www.openpm.info/display/openPM/Canvas
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Gläser, C., Spree, U. (2022). Finding Access Points for Data Literacy: The Example of the ERASMUS+ Project DaLiCo (Data Literacy in Context). In: Kurbanoğlu, S., Špiranec, S., Ünal, Y., Boustany, J., Kos, D. (eds) Information Literacy in a Post-Truth Era. ECIL 2021. Communications in Computer and Information Science, vol 1533. Springer, Cham. https://doi.org/10.1007/978-3-030-99885-1_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-99885-1_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-99884-4
Online ISBN: 978-3-030-99885-1
eBook Packages: Computer ScienceComputer Science (R0)