A work integrated learning content framework for clinical neurophysiology technology in South African universities of technology
| dc.contributor.advisor | Orton, Penelope Margaret | |
| dc.contributor.advisor | Prakaschandra, Dorcas Rosaley | |
| dc.contributor.advisor | Marais, S | |
| dc.contributor.author | Van der Walt, Christelle | |
| dc.date.accessioned | 2025-05-21T08:09:14Z | |
| dc.date.available | 2025-05-21T08:09:14Z | |
| dc.date.issued | 2024-08 | |
| dc.description | Submitted in fulfilment of the requirements for the Master of Health Sciences: Clinical Technology, Durban University of Technology, Durban, South Africa, 2023. | |
| dc.description.abstract | INTRODUCTION Clinical technology (CT) is a group of seven specialist professions dealing with diagnosis and monitoring of human organ system function and diseases. Clinical neurophysiology (CN) is one of these professions and uses multi-modality test investigations of the brain, peripheral and central nervous system, and muscular system, to diagnose and monitor neurological disease. Since the origin of formal training, specialist learning in one of these categories has occurred during a period of work-integrated learning (WIL) after a combined didactic period at one of the three South African universities of technology that offer this qualification. The duration of this period has fluctuated over time. Currently this is set at 3 840 hours over a 24-month placement period as per the South African Qualifications Authority (SAQA) course registration documents. No previous investigations have been conducted to determine the industry required content of this WIL period or how the testing and monitoring modalities taught support specialist learning. No category specific training frameworks exist to aid training units at any of the current three universities offering this qualification. AIMS AND OBJECTIVES The purpose of this study was to determine the current industry requirements for graduates to integrate into Clinical Neurophysiology private practice upon graduation. This study aimed to determine the core testing modalities to include in an undergraduate clinical technology qualification and how each modality can support learning of related modalities. Related to this, this investigation also aimed to determine embedded skills, knowledge, and personal graduate attributes required for mastering of each of the core modalities. The final objective was to design a learning framework based on the interconnected learning affinity of modalities that incorporates all the required graduate skills that drive achievement of graduate level outcome skill levels as determined by industry requirements. METHODOLOGY A Delphi research study was designed to firstly investigate the historic development of the profession and training, and secondly determine the core testing modalities and related knowledge and skills a current industry aligned qualification should include. A round of unstructured interviews and desk research was undertaken to identify all modalities currently included in university of technology course documents. A total of 23 modalities were identified. This round of data gathering was followed by two Delphi questionnaires. The first questionnaire (Q1) provided clinical neurophysiologists (CNPs) currently in private practice an opportunity to select their preferred core modalities from the list of modalities identified during the first data gathering round. Participants were also able to contribute current industry required outcome skill levels and embedded skills and knowledge required to master each modality. Fifty participants identified a list of 15 modalities as potential core modalities and contributed approximately 1 600 comments on prerequisite skills and embedded knowledge and graduate attributes. The second questionnaire (Q2) reported the findings of the first and provided the 36 participants with the opportunity to evaluate the learning and prerequisite dependence or affinity of interrelated modalities. The participants also reevaluated the required outcome practice skill level for each modality and how knowledge and practical skills from Q1 drive learning of the core modalities. RESULTS At the end of the second questionnaire a total of 13 modalities were identified as core modalities that are essential to master during undergraduate WIL. It was determined that students must be able to perform, report, and interpret the results of the 13 core modalities. Dependence affinity of the 13 core modalities for learning of related modalities was confirmed and the embedded and prerequisite skills driving the mastering of each modality were combined into a learning framework. Results confirmed the historic foundational importance of electroencephalography (EEG) as a prerequisite to learning all the other core modalities. CONCLUSION This was the first study investigating industry required graduate outcome skills for an undergraduate qualification in clinical technology. Through a Delphi study 13 core outcome modalities were identified and the required outcome skills level for integrating into private practice was determined. Participant skills and knowledge contributions were drawn upon to design a driver-based learning framework that can guide the universities and training units in structuring the WIL period for most efficient clinical training time management to achieve the required graduate skills outcomes during the 3 840 clinical training hours. | |
| dc.description.level | M | |
| dc.format.extent | 348 p | |
| dc.identifier.doi | https://doi.org/10.51415/10321/5961 | |
| dc.identifier.uri | https://hdl.handle.net/10321/5961 | |
| dc.language.iso | en | |
| dc.subject.lcsh | Experiential learning--South Africa | |
| dc.subject.lcsh | Education, Higher--South Africa | |
| dc.subject.lcsh | Clinical neuropsychology | |
| dc.subject.lcsh | College students--Training of--South Africa | |
| dc.title | A work integrated learning content framework for clinical neurophysiology technology in South African universities of technology | |
| dc.type | Thesis | |
| local.sdg | SDG03 | |
| local.sdg | SDG04 |
