Meaning-Making in Technology-Enhanced Learning Activities: A Composite Perspective of Technologies and Their Properties and Users’ Representations

Abstract

Technology use in school settings tends to look at various technologies solely as mediators for production and work, rather than to relate them to the patterns of thinking and learning. Some technologies and representations are more overrepresented than others, which signals a more monotonous use [22]. However, recent research indicates that meaning-making (actions and signmaking/learning) in connection with technology use is characterized by a higher level of variety and multiplicity across technologies and their properties and users [9], [13], [14], [22]. There is a need to explore and gain insights into how multimodal technology use can be understood and supported from a more comprehensive perspective. This study aims to examine the use of technologies (hardware and software in combination) in students' meaning-making activities in Swedish schools from a multimodal layer (ML) approach [22]. The research questions are the following: what functional and semiotic properties of the technologies are prompted and drawn upon in use; how are transitions made between technologies, their properties, and users; and what modes of representations are made by individuals in relation to the actions and sign-making activities with different configurations of technologies?The ML framework was used as a vehicle for data gathering and analysis from its five components: technologies, technologies' functional properties, technologies' semiotic properties, modes of representation, and activities. Empirical data consisted of 8 hours of classroom video recordings and observations on students' use of technologies in their learning activities, and 6 hours of interviews with the students were observed. All data were transcribed into texts-for instance by using word processing software and the video annotation software Transana-for subsequent quantitative content analysis. The layers were used as the first coding categories in processing the transcriptions and as variables in the analysis. The second step of coding was based on keywords (the values -subcategories to the layers) by using the software nCoder. Finally, the program Epistemic Network Analysis (ENA) was used to visualize the connections between the layers [44], [45].The results from the ENA, as expected, are that some functional properties were more frequently used at specific mediating levels with the use of certain technology combinations and had stronger connections to modes of representation and activities than other properties had. Moreover, some functional properties tended to remain at the same mediating level between technologies, while others were entirely altered or even eliminated. The investigations also showed that some categories of technologies and properties were more frequently drawn upon, reflected in the users' modes of representations. In some activities and combinations of technologies, the transitions in the various functions to the semiotic properties were more complicated and had little influence on individuals' meaning-making, as shown in weak ENA conn...

Dissolving the Dichotomies Between Online and Campus-Based Teaching: a Collective Response to The Manifesto for Teaching Online (Bayne et al. 2020)

“…As the transformation of human activities and artefacts are relative to the spatial-temporal conditions, they invite an understanding of when and how meaning potentials change between the technologies and the teachers' and students' meaning-making based on sign-systems (Bezemer and Kress 2016). Thus, the spatial-temporal conditions are constantly multiplied in meanings between these entities, and render a complexity to teaching and learning activities, and will be unravelled here by the multimodal layer (ML) perspective (Schnaider et al 2020;Schnaider and Gu 2021).…”