Is textese a threat to traditional literacy? Dutch youths’ language use in written computer-mediated communication and relations with their school writing (original) (raw)

Table of Contents Acknowledgements Chapter 1. Introduction Part 1. Theoretical background on CMC and literacy Chapter 2. Literacy in the age of computer-mediated communication Chapter 3. Relations between written CMC and literacy: Prior research Part 2. Language use in Dutch youths' written CMC Part 2.1 Data collection Chapter 4. Collecting Facebook posts and WhatsApp chats: Corpus compilation of private social media messages -with W. Stoop Part 2.2 Data analysis Chapter 5. Out-of-the-ordinary orthography: The use of textisms in Dutch youngsters' written computer-mediated communication Chapter 6. Orthographic principles in computer-mediated communication: The SUPER-functions of textisms and their interaction with age and medium Chapter 7. WhatsApp with social media slang? Youth language use in Dutch written computer-mediated communication Part 3. Relations between Dutch youths' written CMC and school writing Chapter 8. Linguistic characteristics of Dutch computer-mediated communication: CMC and school writing compared Chapter 9. Relationships between Dutch youths' social media use and school writing -with W. Spooren and A. van Kemenade Chapter 10. The impact of WhatsApp on Dutch youths' school writing skills -with W. Spooren Chapter 11. Conclusion References Appendices First of all, I would like to express my sincerest gratitude to my supervisors Wilbert Spooren and Ans van Kemenade, without whose expert advice, patience, and guidance I would not have been able to complete this thesis, and who co-authored (a) paper(s) included in this dissertation. Many thanks are extended to fellow PhDs Alan Moss and Laura Hahn, who were the greatest office mates in room E6.23 of the Erasmus tower. Alan was always there to cheer me up with a silly joke or a delicious home-made pastry when my spirits were low, and Laura's two PhD babies made me realize there is more to life than writing a thesis. I would also like to thank the other PhDs from the Dutch department, specifically Paul Hulsenboom, Nadine de Rue, and Marten van der Meulen, and later also Fons Meijer and Adriaan Duiveman, for the fun times we had at pub quizzes and drinks at the CultuurCafé. 'Letterbekjes' ftw! I am grateful to computer wiz Wessel Stoop for his help with the collection of my social media data; without his computational linguistic skills, I would not have been able to collect the WhatsApp chats that provided such a valuable addition to my corpus studies, and the Facebook posts that I can use in future research. My thanks go out to other wonderful colleagues of the Department of Dutch Language and Culture, the Centre for Language Studies, and the Graduate School for the Humanities at Radboud University; former colleagues of Communication and Information Sciences at Tilburg University, in the last year of writing up my thesis; and my current colleagues of Communication and Information Studies at Radboud University, during the very final months of finishing this book. I wish to acknowledge the assistance provided by my student assistants Iris Hofstra, Anne Janssen, Iris Monster, and Nicky Riemens. They helped me double code part of my corpus, input the survey data, type out the 400 (!) hand-written essays and 500 (!!) hand-written stories produced by the participants of my correlational and experimental studies, and create the website for my WhatsApp data collection. Also greatly appreciated were my bachelor thesis students in Nijmegen (Anke de Bruijn, Lianne Görtz, Geke Kloosterziel, Nicky Riemens, Fabiënne Stoffels, and Melchior Twal) and Tilburg (Arianne van Helden, Tess van der Laan, and Alyssa Rosenau), who got inspired by my passion for 'WhatsApp language' and conducted invaluable pilot experiments and follow-up analyses for me. A big thanks once again to the youths who voluntarily donated their social media messages to my corpus, as well as to the 900 students and their teachers of Canisius College, Dominicus College, Karel de Grote College, ROC Nijmegen, and Radboud University for their participation -particularly to those students in the control groups who at first had no clue how colouring mandalas could possibly be part of a scientific study. My gratitude also goes out to the Netherlands Organisation for Scientific Research (NWO), for providing the financial support for my PhD project, including for the many conferences I visited, which helped me become an independent, internationally oriented researcher. 8 Is Textese a Threat to Traditional Literacy ? Chapter 1: Introduction 17 Chapter 11, finally, presents the general discussion, including an overview of the main findings, implications of the results, limitations of the studies presented in this thesis, suggestions for further research, and my current conclusion on the effects of informal written CMC on Dutch youths' school writings. Since CMC has become part and parcel of youths' communicative practices, the socalled "Gr8 Db8" has arisen: people have conflicting opinions on the possible effects of CMC on traditional literacy . As mentioned above, many adults fear that CMC is detrimental to youths' writing skills, or even to (the Dutch) language in general. For example, they believe that too much exposure to non-standard forms in CMC may come to replace the standard representation of words in youths' mental lexicons -or, simply put, may cause them to forget the standard spelling or grammar. Such concerns have been openly expressed in the media , as exemplified in newspaper headlines such as "Techspeak Ruining Kids' Grammar" (Mlot, 2013) and "Help, My Child Writes in Textese" ("Help, mijn kind schrijft in digi-taal," . On the other hand, there are also some linguists who point out the possible language benefits of CMC, such as creativity and playfulness with written language, more motivation to read and write, increased exposure to written texts, and even a greater awareness of letter-sound correspondences in language -the latter due to abbreviations based on sounds, e.g. strax < straks ('later'), suc6 < success ('success') (