Learning Outcomes

Machine Learning

Maria Ingold
AI generated with ChatGPT 4o
  1. Articulate the legal, social, ethical and professional issues faced by machine learning professionals.
  2. Understand the applicability and challenges associated with different datasets for the use of machine learning algorithms.
  3. Apply and critically appraise machine learning techniques to real-world problems, particularly where technical risk and uncertainty is involved.
  4. Systematically develop and implement the skills required to be effective member of a development team in a virtual professional environment, adopting real-life perspectives on team roles and organisation.

SWOT, Professional Skills Matrix and Action Plan

Unit 11

Outcomes

What

My SWOT analysis captured my strengths as a media technology professional with 30 years' experience, opportunities for public speaking, and service as a student representative and module WhatsApp facilitator. It also noted my weakness in balancing quality with self-care, and the threats of course errors and less relevant material (MindTools, N.D.). My skills matrix showed growth in ethics, critical writing, research methods, and statistical analysis in Excel. I enthusiastically engaged in assignments relevant to AI in media.

So What

Despite these achievements, much of the coursework focused on methodology, writing, mathematics, and reflecting, requiring me to seek AI expertise through external sources. Furthermore, module errors hindered efficiency. Balancing coursework with staying relevant meant dedicating time to less relevant topics, impacting self-care and professional growth.

Now What

My action plan aims to mitigate these challenges (Cottrell, 2021). I will continue to combine industry and academic research, build expertise through public speaking, and supplement with external training. My student WhatsApp group supports collectively addressing course errors. However, as I prioritise knowledge, academic quality, and timely delivery, my biggest challenge remains allocating time for self-care.

e-Portfolio and Reflection

Unit 12

Outcomes

What

This e-portfolio reflected on research method processes. Appraising issues (1) through ethics and survey use reflections showed practical insights from industry research, such as OECD.AI's (2024) AI Principles, were often missing in academic contexts. Moreover, employing academic investigation (2) in the literature review demonstrated the need for industry examples like Steck et al. (2021).

So What

The collaborative learning loop process highlighted the importance of thorough review and critical evaluation (3), as seen in the misinterpretation of Milyavsky et al. (2017) and conflict of interest by Godlee et al.'s (2011) publisher. These exemplified the potential for researcher bias or error. Critically evaluating Dawson's (2015) and Saunders et al.'s (2019) methods (4) for the research proposal helped me ascertain suitability. Discovering Page et al.'s (2021) PRISMA guidelines and comparing industry and academic research helped me identify a critical research gap.

Now What

I will apply critical evaluation skills to all stages of my research, using tools like PRISMA guidelines to systematically structure reviews. I will continue seeking feedback to refine my writing and critical thinking skills. Integrating industry and academic research will help me maintain a balanced perspective and ensure professional applicability.