e-Learning in Phoniatrics and Speech-Language Pathology: Exploratory Analysis of Free Access Tools in Augmentative and Alternative Communication
Bibliographic record
Abstract
Background: Augmentative and alternative communication (AAC) is a therapeutic approach and modality of expression for patients with limited or no expressive language. Speech-language pathologists and phoniatricians need to be competent in AAC to treat patients with complex communication needs. For knowledge acquisition and enhancement in AAC, a significant number of e-learning tools are available. To improve e-learning in AAC, it is essential to understand the attributes of these tools, such as formats, content areas, learning styles, or learning goals. However, these structures have yet to be investigated. Objective: With this study, we aimed to (1) explore free access AAC e-learning tools that are appropriate for students and professionals of phoniatrics and speech-language pathology; (2) gain insight into formats, content areas, learning styles, and learning goals; and (3) investigate structural differences within and between basic and advanced learner level. Methods: In 2023, we conducted a systematic web-based search with defined search terms in PubMed, peDOCS, Google Scholar, Google, the Apple App Store, and the Google Play Store in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines and piloting a protocol for data abstraction and validation. Inclusion criteria were free access, a mandatory minimum AAC content, and the use of the English or the German language. Social networks, video-sharing platforms, blogs, and forums were excluded. We analyzed formats (websites, online courses, apps, and podcasts), content areas (types of AAC, diagnostics, therapy, and other content areas), learning styles (visual, auditory, and audio-visual), and learning goals (receptive and performative) within and between basic and advanced level tools. Results: We identified 131 tools, of which 57 (43.5%) were basic level and 74 (56.5%) were advanced level. Of these 131 tools, 105 (80.2%) were websites, 21 (16%) were online courses, 3 (2.3%) were apps and 2 (1.5%) were podcasts. Only 12 out of 74 (16.2%) tools for advanced learners offered performative tasks. For basic learners no such tasks could be identified. For learning style, all basic tools and most of the advanced level tools were "visual (text)" (57/57, 100% basic vs 66/74, 89.2% advanced). In terms of content, advanced level tools pertained more often to "diagnostics" (28/57, 49.1% basic vs 65/74, 87.8% advanced) and "therapy" (17/57, 29.8% basic vs 64/74, 86.5% advanced). Advanced level courses were more likely online courses (2/57, 3.5% basic vs 19/74, 25.7% advanced) and more often showed audio-visual learning styles compared with basic level tools (5/57, 8.8% basic vs 27/74, 36.5% advanced). Conclusions: Our study showed that free-access AAC tools for phoniatrics and speech-language pathology varied in formats, content areas, learning styles, and learning goals. Furthermore, we found differences within and between learner levels. Thus, we established a basis for future research in e-learning in AAC.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".