~ [[Works]] *Business Innovation Live Project* >[!External Links]+ >[Briefing](x-devonthink-item://B06CC854-E95D-41A0-B34E-AA7BD7E23237) >[DEVONthink Folder](x-devonthink-item://9B22AE9F-8BC0-48D5-832A-22548FFCF15E) >[[BILP Learning Outcomes]] >[FINAL BILP REPORT](x-devonthink-item://6B4A6DD1-705B-408A-A138-FF0E57B36C02) >Final [reflections report](x-devonthink-item://8171C676-1988-4B9B-8E32-9C4E14F4A6CE). ## Lectures - [[BILP Briefing]] - [[Literature Review]] - [[Ethical Approval]] - [[Research Ethics and Philosophy]] - [[Qualitative and Quantitative data collection]] ## Assessments Two key dates- 25th March and 30th September - [[BILP Assessment 1 - Project Proposal]] - 25th March - [[BILP Assessment 2 - Critical Reflection]] - 30th Sept 2022 - [[BILP Assessment 3 - Individual Report]] - Sept ## My Work ### Proposal - [[Potential BILP Research topics]] - [[BILP proposal first draft]] - [[BILP proposal second draft]] - [[BILP proposal third draft]] ### Main BILP Project [[BILP Project final draft aims, objectives and research question]] 1. [[1. BILP Introduction]] 2. [[BILP Literature Review]] 3. [[University Organisation Design]] 4. [[2.2 Students' unions and their partnership with universities]] 5. [[2.3 Criticisms of bureaucratic organisation design]] 6. [[3. BILP Research Methodology and Design]] 7. [[4. BILP Results]] 8. [[5. BILP Conclusions]] #### Notes for BILP - [[BILP Arguments Hypothesis what I believe.]] - [[Excerpts from my BILP]] ### Reflection paper (1500 words) Notes: - [[Reflections for BILP reflective report]] - [[BILP Reflective Report v1]] ## Notes - Very quickly I will be more knowledgeable than the supervisor on this topic. - Look into research questions once the literature review has been done. Don't want to know these today. - Use a simple numbering system for each chapter - Do not do any data collection until ethical approval. - Do this as soon as the [[BILP Assessment 1 - Project Proposal|project proposal]] is submitted. - Eliminate bias in the data collection is key. More key than eliminating bias in the hypothesis.