Digital Humanities Pedagogy: Integrative Learning and New Ways of Thinking About Studying the Humanities
Bibliographic record
Abstract
This paper presents two case studies to reflect on and evaluate the use of integrative i, reflective ii, and object-based learning iii pedagogies to scaffold the learning experience of students in an established core module for the MA/MSc in Digital Humanities programme at UCL. We deliver a research-led curriculum to an international cohort of students from widely differing backgrounds and qualifications. How do we accommodate learners at different skills levels and engage them all to make their learning experience meaningful? In line with the Scholarship of Teaching and Learning (SoTL) an important aspect of our practice is that research underpins pedagogical decisions. Following lectures designed to introduce provocative questions, students are required to work on their own, then in a group to reflect on their existing knowledge and construct new knowledge, before presenting their thoughts. This problem-based approach is informed by reflective and social-constructivist theories of learning. Secondly, object-based learning is made possible and supported by the many teaching based collections at UCL; students compare and contrast physical and online representations of objects and their systems followed by seminar discussions to demonstrate how they have been able to apply their learning in a new context. These all have a strong theoretical underpinning with a firm focus on ‘how we learn’ and particularly in a ‘social context’ iv; here students learn from their interaction with each other; “[…] the educational process has two sides – one psychological and one sociological; and that neither can be subordinated to the other or neglected [...] Education is a collaborative reconstruction of experience”. v These pedagogies help build a community of learners by instilling the cooperative, collaborative, and reflective skills needed for them to continue their education beyond the academy: the skills for life and living. i Huber Taylor, Mary, and Pat Hutchings. 2004. “Integrative Learning Mapping the Terrain.” The Academy in Transition. Washington: Association of American Colleges and Universities. ii Brockbank, Anne, and Ian McGill. 2007. Facilitating Reflective Learning in Higher Education. Maidenhead, England; New York: McGraw Hill/Society for Research into Higher Education and Open University Press. iii UCL (2013), ‘Object-based learning’ <http://www.ucl.ac.uk/teaching-learning/teaching-learning-methods/object-based-learning> (accessed 06/05/2014) iv Vigotsky I (1978) Mind in Society: The development of Higher Psychological Processes. Cambridge, MA: Harvard University Press. v Dewey J (1959) Dewey on Education, Teachers College Press, Columbia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".