Prompting skill built by the user, and a widening repertoire of tools
Respondents in every group attribute improved results to their own learning: prompts have become more specific and goal-directed, extended exchanges are sustained more deliberately, and use has moved from a single tool to a set of tools selected for particular purposes. Explaining a task to the model is described as constituting a learning experience in itself.
Record
- Level
- Micro
- Domain
- AI Literacy and Professional Development
- Country
- Multiple countries
- Context
- Higher education
- Maturity
- Established
- Scalability
- Piloted
- Transferability
- Embedded
- Source report
- R3
Account of the practice
Capacity building is documented at the institutional level as courses and certificates and at the national level as platforms. This record covers the competence that respondents report acquiring without any of these, and the distinction is worth preserving because the two do not describe the same thing. A course teaches what a tool is, whereas what respondents describe here is knowing how to work with one.
Three components recur. Prompts become specific and goal-directed rather than open. Extended exchanges are sustained rather than restarted, which respondents connect to an increase in trust. Tools become differentiated, with a movement away from a single general assistant towards a set in which each is used for the task it suits.
One account gives the practice its pedagogical significance. A student describes the effort of explaining to the model what it should do as sometimes constituting a learning experience in itself, and connects this to a firmer conviction that the manner in which they use the tool is effective. Articulating a task in terms sufficiently precise for a machine to act upon is a form of rehearsal, and this is the only point in the material at which a respondent identifies it as such.
Respondents also attribute part of the improvement to the models rather than to themselves, and the report treats the two explanations as distinct themes. The present record covers only the part respondents claim as their own.
Source trail
The source on which this record rests, the place in the document and the sentence found there. Quotations are searched for mechanically in the source file and the page on which they were located is recorded.
- 01R3 · Report on trends in policies and practices on the use of LLMs and generative AI in the partnership: Third report (draft)ADMIT (Erasmus+, EADTU)Section 3.2.5Quotation located in the source
I've learned how effective prompts work and that the effort involved in explaining to the AI what it should do can sometimes be a learning experience in itself.
The respondent identifies the articulation of a task as the learning, which is the strongest pedagogical claim any participant makes for individual use.
- 02R3 · Report on trends in policies and practices on the use of LLMs and generative AI in the partnership: Third report (draft)ADMIT (Erasmus+, EADTU)Section 3.2.5Quotation located in the source
I know how to prompt better, I know how to maintain an extended conversation better.
Sustaining an exchange is named as a separate skill from composing a request, which is the distinction the record rests on.
- 03R3 · Report on trends in policies and practices on the use of LLMs and generative AI in the partnership: Third report (draft)ADMIT (Erasmus+, EADTU)Section 3.2.5Quotation located in the source
I was mostly using chatgpt earlier. Now, i try different ai tools like gemini, notebooklm etc.
The move from one assistant to several is stated by a student, and the same move is described by staff, which shows the differentiation is not confined to one group.
Evidence
The reported evidence on the effect of the practice. Evidentiary strength varies between practices; it is reproduced here as the source reports it.
Named by the report as one of the most frequently mentioned themes under change over the preceding year, with verbatim quotations from support staff, teachers and students in more than one country.