English Teachers’ perspectives on infusing ICT in Engineering Graphics and Design pedagogies using the TPACK Framework
Bibliographic record
Abstract
The 21st century and the 4th Industrial Revolution have necessitated a shift in pedagogies, highlighting the importance of integrating Information and Communication Technology (ICT) into education. This study explored Engineering Graphics and Design (EGD) teachers’ perspectives on the use of ICT in EGD classrooms, aiming to recommend strategies for effective integration using the Technological Pedagogical and Content Knowledge (TPACK) framework. Using a qualitative approach, data were collected from nine EGD teachers across secondary schools in the uMgungundlovu district of KwaZulu-Natal, South Africa, through semi-structured interviews and classroom observations. Thematic and descriptive analyses revealed that ICT plays a vital role in enhancing EGD instruction. Teachers demonstrated strong Technological Knowledge (TK) and effectively used tools such as AutoCAD and simulations to facilitate learners’ understanding of complex concepts. They also showed competence in aligning technology with pedagogy (TPK) and content (TCK). However, their efforts were often constrained by limited infrastructure and outdated resources. These systemic challenges hinder the full realisation of ICT’s potential in classrooms. The study recommends that the Department of Basic Education prioritize investment in ICT infrastructure and ensure equitable resource distribution. It also underscores the need for continuous professional development rooted in the TPACK framework and the creation of digital teaching resources. Furthermore, establishing professional learning communities is essential to foster collaboration and improve the integration of ICT in teaching practices. These measures are crucial for empowering teachers and preparing learners for the demands of a technologically driven world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".