A framework for writing learning agreements

Clear, Tony; McDermott, Roger; Parsjo, Elin; Cajander, Åsa; Daniels, Mats; Lagerqvist, Nanna

doi:10.1109/fie.2016.7757718

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…Learning agreements (LA), learning plans or student contracts, strive to be transformative educational tools that aim to place students in control of their learning journeys (Clear et al, 2016). LAs provide incremental steps through which students assume ownership of their learning, fostering a sense of accountability, community belonging, and shared expectations with their teachers (Nielsen et al, 2022).…”

Section: Learning Agreementsmentioning

confidence: 99%

A Learning Agreement for Generative AI Use in University Courses: A Pilot Study

Beardsley,

Amarasinghe,

Theophilou

et al. 2024

Preprint

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The rapidly evolving landscape of Generative AI (GenAI) tools necessitate continuous vigilance and adaptation by educators. This dynamism requires stakeholders to stay up to date with developments to address emerging issues effectively, creating complexity in managing the responsible and ethical use of GenAI. This paper presents a pilot study involving the use of student learning agreements for governing GenAI use in a first-year engineering degree course. The learning agreement contains ethical and social considerations students agree to make if they decide to use GenAI in the course. As part of the pilot study, pre-post surveys and student artefacts – a group assignment adapted to accommodate GenAI use – were analysed. Results show that the vast majority of students were in favour of the learning agreement approach both at the start and upon completion of the course. However, 7 of 17 groups did not use GenAI in their assignment. Of the 10 groups that did, only 1 acknowledged GenAI limitations in adherence with the learning agreement. A thematic analysis of student suggestions for improving the learning agreement approach include suggestions for making the agreement easier to understand and adhere to (e.g., providing specific examples, reengaging with the agreement during the course). Overall, findings suggest that learning agreements have the potential to offer an interface through which student decision-making can be supported and interactions among students, educators, researchers, and policy makers related to the ethical and societal challenges of GenAI can take place.

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Section: Learning Agreementsmentioning

confidence: 99%

A Learning Agreement for Generative AI Use in University Courses: A Pilot Study

Beardsley,

Amarasinghe,

Theophilou

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…The "Opportunity narrowed" thematic network can in many ways be seen as the reason behind the most of the pedagogical interventions that have been added to the Uppsala course setting over the years. Perhaps the most prominent one being the inclusion of learning agreements based on a set of professional competencies [Clear et al 2016]. One of the nine competencies students are prompted to choose to focus on is "Thinking skill," which is closely related to the ideating concept (cf.…”

Section: Reflections On Transferabilitymentioning

confidence: 99%

Searching for Global Employability

Isomöttönen

Daniels

Cajander

et al. 2019

ACM Trans. Comput. Educ.

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Literature on global employability signifies "enabling" learning environments where students encounter illformed and open-ended problems and are required to adapt and be creative. Varying forms of "projects," co-located and distributed, have populated computing curricula for decades and are generally deemed an answer to this call. We performed a qualitative study to describe how project course students are able to capitalize on the promise of enabling learning environments. This critical perspective was motivated by the circumstance of the present-day education systems being heavily regulated for the precipitated production of human capital. The students involved in our study described education system-imposed and group-imposed narratives of narrowed opportunities, as well as many self-related challenges. On the other hand, students welcomed autonomy as an enjoyable condition and linked it with motivation. Whole-group commitment and self-related attributes such as taking care of one's own learning appeared as important conditions. The results highlight targets for interventions that can counteract constraining study conditions and continue the march of projects as a means to foster complex learning for the benefit of students; and professionalism in global software engineering.

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“…This is important work for those of us who proudly state the graduate attributes that our students are meant to possess on completion of their degrees. Often these attributes are expressed in terms of broad competences such as "learning how to learn" [8]. Competences have been expressed in Ref.…”

Section: A Continuum Of Eight Gse-ed Special Issue Articles 31 Fullymentioning

confidence: 99%

Global Software Engineering Education Practice Continuum Special Issue of the ACM Transactions on Computing Education

Clear

Beecham

2019

ACM Trans. Comput. Educ.

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We are pleased to introduce this Special Issue on Global Software Engineering Education published by the ACM Transactions on Computing Education (TOCE) that focuses on educational practices to prepare students for a global workplace. This issue comes at a time when universities are recognizing the need to provide courses that address the challenges of distributed development and presents research that will facilitate course leaders currently running, or embarking on, Global Software Engineering Education (GSE-Ed).

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A framework for writing learning agreements

Cited by 7 publications

References 21 publications

A Learning Agreement for Generative AI Use in University Courses: A Pilot Study

A Learning Agreement for Generative AI Use in University Courses: A Pilot Study

Searching for Global Employability

Global Software Engineering Education Practice Continuum Special Issue of the ACM Transactions on Computing Education

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