Formative assessment has been shown to improve student engagement and learning outcomes across several subject domains in K-12 education. However, its effectiveness within the subject domain of digital tooling remains understudied. This research investigated the effect of computer assisted formative assessment on learning outcomes and behavioral student engagement, with the latter as a potential mediating variable, within the subject domain of digital tooling.

This research conducted a quasi-experiment with 122 second-grade students from a Havo/Vwo high school during a course on Google Spreadsheets. The experimental group had access to a button that let the computer instantly check their homework and provide feedback, while the control group did not. At the end of the course, students in the experimental group completed a questionnaire to share their experiences.

This research found no significant effects of the intervention on behavioral student engagement and learning outcomes, nor was a mediated relationship established. However, students did report several cognitive and metacognitive benefits. Namely: enhanced motivation, enhanced self-regulated learning, enhanced autonomy, feedback that helped them move forward and an improved understanding of the material. On the other hand, they reported some downsides. Namely: increased time consumption, a lack of added value and a lack of feedback quality.

Since this research did not find effects of computer assisted formative assessment similar to those observed in other subject areas, it raises the question of whether the subject domain of digital tooling interacts differently with this type of intervention. Further research with a greater sample size and statistical power is needed to explore this possibility. Future research could investigate which characteristics make this subject domain distinct, in which contexts within digital tooling this type of intervention is most effective and which benefits it should aim to provide.

As technology advances, automated systems become more autonomous which leads to a higher interdependence between machine and human. Much research has been done about trust between humans and trust of humans regarding machines. An interesting question that remains is how the behavior of an agent influences human trustworthiness in a human-agent collaborative setting. The research presented by this paper contributes to the understanding of this area. It investigates a specific behavioral trait using the following hypothesis: friendly behavior of an agent improves human trustworthiness. Here, trustworthiness is broken up in the constructs: ability, benevolence and integrity.

An experiment has been conducted using a collaborative Search and Rescue game. The following behaviors of the participants have been measured:
- Ability: speed and effectiveness;
- Benevolence: communication, willingness to help, agreeableness to advice, responsiveness;
- Integrity: truthfulness.
Furthermore, a likert scale has been used to measure the participants' own perception of their trustworthiness. The experiment is conducted with 20 participants in the control group, where the agent spoke in a neutral manner, and 20 in the experimental group, where the agent instilled empathy, stimulated collaboration, encouraged the participants and was affectionate.

The research has shown a significant improvement in the experimental group only for communication and willingness to help. This gives some indication that a friendly agent only slightly improves the trustworthiness of a human. However, the research has some limitations that might also explain the lack of significant results. Firstly, it is unclear to what extent the measures truly measured the constructs of trustworthiness. Secondly, to create a friendly agent, theories from organizational and social psychology are used, which are mostly focussed on human-human relationships, instead of human-agent relationships. Finally, Some confounding variables may have had an impact, like lag in the game and the participant not properly reading the agent’s messages.