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Friday - 11.35: session 20 – Mathew Toll & Shi Chunxu is back on, in B48, replacing Sha Xie.

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Thursday, July 4 • 11:30am - 12:30pm
The sum of its parts: An autonomy analysis of combined app use in primary schools

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Educational apps are one of the fastest growing areas of technology use in the classroom. However, the quality of apps and contribution to learning continues is under question. This is in part because research has struggled to show clear benefit of app use in learning. In reality apps are used in combinations and possible benefits are likely to be from use of multiple apps (Howard, et al., 2018). We argue that app use needs to be understood as a combined practice, rather than individual apps. Given the acknowledge importance of quality early learning and the high use of apps among young children, it is critical that a better understanding of this use in learning is developed.

To explore this issue, this paper presents an analysis of app use data from 30,000 Android tablets in primary school classrooms (Years K-3; Ages 5-9) across Australia, between 2015 and 2017. Data were fist clustered to identify patterns of use. Five unique usage patterns were identified (see Howard et al., 2018). The current analysis further explores these clusters and usage types to understand their relation to learning using the concept of Autonomy. ‘Autonomy begins from the simple premise that any set of practices comprises constituents that are related together in particular ways’ (Maton & Howard, 2018, p. 6). Each of these apps can be understood by its position (positional autonomy [PA]) within the learning context and its relation (relational autonomy [RA]) to other constituents, specifically how insulted they may be. These can be understood along a continuum as stronger or weaker relations. Strength of positional autonomy was based on whether the app was aligned with curriculum (PA++), if it was generally educational (PA+), if it was not explicitly educational (PA-) or if it was non-educational (PA--). Relational autonomy was assessed in regard to whether an app had an explicit educational use (RA++), had a general educational use (RA+), the use was not necessarily educational (RA-), or if it was explicitly non-educational (RA--). Using a modified walk-through method, apps were coded for PA and PA (Light et al., 2016). Results were then plotted on the cartesian plane based on this analysis.

Each of the five clusters showed a different distribution of apps across the cartesian plane. All of the clusters showed some use of educational apps, arcade games and personalization tools. Two of the clusters included a high occurrence of education-focused apps (PA++/+, RA+), many of the apps fell in the sovereign code and were strongly related to learning. However, they were typically only apps for practicing numeracy and literacy. These typically have very little positive effect on learning (e.g. Domingo & Gargant, 2016). Apps coming from outside of learning (PA-), such as Minecraft and Word processing, but used for educational purposes (RA+), fell into the introjected code. These apps were more likely to elicit higher order thinking and organization of information, which suggests deeper learning. Two clusters included use of these apps, along with numeracy and literacy, and arcade game apps. These clusters had a wider range of learning opportunities and would be more likely have a stronger overall relation to quality learning.

Findings from this research suggests that combined app use including apps that are not designed for education, but used for educational purposes, may be more beneficial in learning than more ‘education’ apps. Further research broadening this analysis to include other elements of the educational context, such as other technologies and teacher practice will be conducted. Given that apps are used across a range of international education contexts, findings from this analysis have the potential to inform technology integration and learning design internationally.


Thursday July 4, 2019 11:30am - 12:30pm
Room B45

Attendees (4)