Technology And Teacher Education For A Knowledge Era: Mentoring For Student Futures, Not Our Past
Bibliographic record
Abstract
Three initiatives are described that focus on cultivating inquiry based learning with technology for student teachers. The article describes an approach by a Faculty of Education to the design, development, implementation, and evaluation of media rich learning experiences and research projects. Descriptions are provided of the type of work that student teachers complete. Emphasis is on using technology as a medium for thinking, creation, and invention rather than productivity. The main goal is to foster closer connections between campus and field experiences by cultivating collaborative relationships between university faculty, classroom teachers, and student teachers. ********** Educators need to rethink how student teachers are prepared for the knowledge era. Today's dominant information and communication media are highly interactive, and include international networks, digital video and audio, and hypermedia. Unlike broadcast media of the recent past, digital technologies and the Internet enable both adults and children to author, publish, and freely exchange their stories using multiple media with a global audience. Digital media and network technologies represent a major communications revolution and integration for teaching and learning demands and requires us to question conventional methods and approaches to schooling. Today's digital media requires us to reconsider how to enable students and student teachers to take advantage of unregulated online resources, and contribute to and extend those resources as they share their knowledge and perspectives with the world. Educators must examine school and campus structures and instructional approaches that privilege textual forms of literacy while largely ignoring hypermedia and online forms of discourse. An important job for all educators is to enable learners to author using the media of their time. It is not enough to teach today's children in ways we were taught because they live in a different age. Rushkoff (1996) calls them Screenagers: today's children have been born into a culture mediated by the television and the (p. 3). Screenagers participate fluidly in online, interactive digital environments and virtual spaces--the rapid-fire, nonlinear, chaotic, multisensory world of digital media. Screenagers invent uses for computers and networks that adults often do not anticipate and frequently misunderstand. What educators first assumed children needed from us--careful instruction, step-by-step activities, and computer lessons developed with a close eye to scope-and-sequence--is often exactly what gets in their way (Clifford, Friesen, & Jacobsen, 1998). At home, much like the adult work experience, today's children are multitasking and exchanging documents for social purposes using wireless networks, personal data assistants, digital video and audio devices, and distributed gaming environments. We must examine the implications of these daily interactions with technologies for schooling and for Faculties of Education. How are student teachers taught to leverage today's digital technologies for their own, and for children's, learning and collaboration needs? Wouldn't it be nice for teacher educators to have a crystal ball to guide planning and decisions on how to prepare teachers how to take advantage of technology in their professional roles? However, even with such a time-bending device, we would likely confirm what we already know--there are precious few in today's classrooms, and few set models about what teacher graduates will encounter in their first classroom populated by Screenagers. About the only certainties we can count on are that teachers' professional lives will be characterized by unstructured problems and unpredictable hourly and daily events. Classroom teachers have reflexive roles in increasingly complex, multi-layered and distributed learning organizations that include colleagues, students, parents, and increasingly, the global community. …
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".