Logbook #1

In the context of digital learning environments, immersive technologies such as mixed reality (MR) and respective personalized content are becoming increasingly important. Current research suggests that taking individual learning preferences into account can help to increase motivation. An exploratory study we conducted investigated whether personalized representations in an MR-based gallery view that are adapted to visual or kinesthetic learning preferences lead to higher motivation compared to a standardized, non-personalized version.

Research question and hypothesis
The overarching sub-research question was: Can a specially personalized presentation in an XR gallery view promote motivation more strongly than a standardized presentation? The corresponding hypothesis was as follows: If the gallery view takes into account the individual learning preferences of the users through adaptation (kinesthetic or visual presentation), the motivation to learn increases more than with a standardized, non-personalized overview.

Experimental setup
Three prototypes for the presentation of information overviews in an XR environment have now been developed as part of a ZIM-funded project. H0 was a standardized, non-personalized version. H1 was adapted to visual learning preferences (primarily through the use of a timeline and coherent image anchors), H2 took kinaesthetic aspects into account (i.e. an explicitly spatial arrangement of elements and navigation mechanisms). The participants (n = 9) underwent H0 and either H1 or H2 in randomized order. A corresponding pre-selection had already been made - in other words, it was determined in advance who was visually inclined and who was more aesthetically inclined. After the test was carried out, qualitative interviews and a quantitative survey were also conducted, the results of which we ultimately prepared in the form of an appropriate and professional evaluation.

Qualitative survey
The interviews were analyzed on the basis of Mayring's qualitative content analysis. The categorization was carried out deductively along four main categories: (1) Perception and initial reactions, (2) Comparison of presentation forms and usability, (3) Motivational influences and usage preferences, and (4) Personalization and individual adaptation. A total of ten deductive codes were used, including “initial perception”, “comparative differentiation”, “motivational factors” and “desire for individualization”.

Quantitative survey
The quantitative data was collected using a Likert scale based on items from the Intrinsic Motivation Inventory (IMI) and the Self-Determination Theory (SDT). A one-sample T-test was carried out against the neutral mean. The scales covered aspects such as interest, enjoyment, perceived fit with learning preference as well as understanding and use of the content presented.

Quantitative analysis
In cluster A (“fun, interest and fit”), the personalized presentation was rated significantly more positively than the comparison value of the scale (M = 5.48, SD = 1.06), t(8) = 4.21, p = .003. The effect size according to Cohen's d is 1.40 and thus indicates a very large effect. In cluster B (“understanding and use”), on the other hand, no significant effect was found (t(8) = 0.77, p = .464), and the effect size (d = 0.26) also indicates a small effect.

Qualitative analysis
The qualitative analysis confirmed the results of the quantitative study. The personalized version was perceived by most participants as more motivating, clearer and more natural. The spatial embedding, the link to their own usage context and familiar interaction patterns were particularly positively emphasized. At the same time, it became clear that the standardized version was perceived as artificial, overloaded or more difficult to navigate. In many cases, participants expressed a desire for further individualization (e.g. thematic relevance, visual adjustments, comparison functions), which was not yet reflected in the adapted variants H1 and H2.

The results support the hypothesis with regard to the motivational effects of personalized presentations. The visual variant (H1) in particular was experienced as more pleasant and motivating. The positive ratings in cluster A (“fun, interest and fit”) suggest that the personalized presentation can specifically contribute to increasing the motivation to use the product.

Despite the small sample size (n = 9), a significant difference was found for cluster A compared to the neutral mean. However, the t-test is only meaningful to a limited extent due to the small sample size, as even individual outliers can strongly influence the mean value. In this context, the effect strength according to Cohen's d is more meaningful: with a value of 1.40, there is a very large effect, which can be considered a robust indication of a strong effect even with small samples.
There was no such effect in cluster B, which may be related to the technically and didactically not yet fully developed implementation. Although the personalized presentation enabled more visual orientation, it did not automatically support a deeper understanding or more intensive use of the content.

The qualitative interviews confirm this picture: While personalized presentations were very well received emotionally and in terms of design, the content potential was not yet fully exploited. In particular, the lack of depth of information and occasional technical faults (e.g. with sound, navigation or loading times) were repeatedly criticized. The underlying narrative was also not fully penetrated, which urgently needs to be improved for future testing.

The results of this study show that personalized displays in XR information rooms have the potential to make the use of MR training more enjoyable and thus also have a positive influence on user motivation. In particular, the visual adaptation to individual learning preferences contributed to a higher perceived fit, greater interest and more enjoyment of use. Follow-up studies with a larger sample, technical optimization and more targeted didactic design are required to deepen the results. In the long term, the findings could contribute to the improvement of digital learning environments in the area of XR and in combination with strong AI.

Since we are keen to communicate our research as transparently as possible, the ongoing category of the logbook is an important component in achieving that goal. We will regularly update you on the steps we have taken and share our findings with the general public.