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Professional Perspectives: Electronic Engineering

Professional Perspectives: Electronic Engineering. Paul Spencer Dean of School, Electronic Engineering Kal Winston* Adviser, Study Skills Centre. Initial Action. M eetings between E ngineering and SSC staff Exam Review workshop with students Examination of sample dissertations & reports

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Professional Perspectives: Electronic Engineering

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  1. Professional Perspectives: Electronic Engineering Paul Spencer Dean of School, Electronic Engineering Kal Winston* Adviser, Study Skills Centre

  2. Initial Action • Meetings between Engineering and SSC staff • Exam Review workshop with students • Examination of sample dissertations & reports • Difficulties appear to include • Study skills, approaches to learning • Critical thinking • Academic literacy • Application of ideas • Following instructions • Self-discipline

  3. Professional Perspectives • 10-credit first year, first-term module • 12 x 2-hour sessions • Aims: • Assist students with their approach to other modules, and help them develop the skills needed to succeed in Electronic Engineering courses. • Provide students with transferable skills needed for employment as engineering professionals.

  4. Group/Individual • Students randomly assigned to a small group of 4 students, work together throughout the module. • Assess both individual and group work. • Groups meet between classes (minimum of four meetings), members take turns recording minutes.

  5. Weekly workshops on… • Time management • Critical questioning • Working with lectures • Explaining terminology • Library resources • Referencing and plagiarism • Exam techniques • Writing minutes • Data analysis • limits, scales, errors, dimensional analysis • Report writing – structure, writers’ moves • Draft reports • Peer-assessment • Formative feedback • Presentation skills • Creating and using rubrics

  6. Assessment 1, Project • Project Report, 2500 words - 40% • 10% for submission of draft report • 30% for final report • Groups select their own project topics. • Each group crafts a clear research question, which is then divided into one sub-question per group member. • Most sessions include work contributing towards final project.

  7. Assessment 1, Project • Week 3, groups submit project brief, outlining their project, stating their research questions. • Each group member writes a report on his/her chosen sub-question. • Week 7, individuals submit draft version of their individual reports • Grade each other’s drafts using rubric • General feedback on common errors • Final versions of the report submitted 3 weeks later.

  8. Assessment 2, Portfolio 20% of module grade, tasks based on weekly workshops • Build ‘generic skills’ and skills for project • Time management • module assessments,project milestones • Asking questions • explore lectures, create research questions • Define and explain terminology • from lectures, key project concepts • Library resources, references, plagiarism, paraphrasing • summary of and references for two scientific reports • Data analysis assignments • feel for equations, data presentation • Minutesfrom group meetings, contributions to discussion forums, module reflection, Peerwise

  9. Assessment 2, Portfolio 20% of module grade, tasks based on weekly workshops • Build ‘generic skills’ and skills for project • Time management • module assessments,project milestones • Asking questions • explore lectures, create research questions • Define and explain terminology • from lectures, key project concepts • Library resources, references, plagiarism, paraphrasing • summary of and references for two scientific reports • Data analysis assignments • feel for equations, data presentation • Minutesfrom group meetings, contributions to discussion forums, module reflection, Peerwise

  10. Assessment 3, Presentation • Oral presentation – 20% • 10-minute group presentation • Synthesis of members’ project work. • Rubric developed in class • Groups and teachers mark each presentation, averaged for group score.

  11. Assessment 4, Data Analysis test • In-Class Test – 20% • Based on Data Analysis Techniques sessions • order of magnitude estimations • taking limits • dimensional analysis • systematic and random errors • graphical display methods.

  12. Successes • Better understanding of students needs, strengths and weaknesses • Inter-departmental collaboration – design and delivery of module • Lively, interactive class discussions • Opportunity to give feedback on students’ writing • Good outcomes for: • referencing and plagiarism • note taking • revision advice • group presentations

  13. Challenges and Solutions, 1 • Variable attendance/participation • Late admittance to course • 9am Thursday (Weds p.m. free) • Affected group work • Non-completion of portfolio tasks, so some students missed incremental build-up towards project • Next time: less reliance on groups, stricter deadlines for portfolio tasks

  14. Challenges and Solutions, 2 • Overly ambitious goals – data analysis • Presented too many ideas • Students’ understanding weaker than expected (e.g. derivative as rate of change) • Poor test performance • Next time: restrict to narrower range (limits, units, scales), more examples and practice in class • tie-in with critique of journal article

  15. Challenges and Solutions, 3 • Presentations – group members not all engaged, some free-loading • Related to project – if that was poor, adversely affected presentations • Next time: in pairs, shorter presentation, explain a key engineering concept, and how it can be applied in practice • builds on prior exercise on explaining terminology

  16. Challenges, 4 • Overly ambitious project • Many had never read a journal article, much less critically appraised one • Too much choice for project • Too long • Underestimated problems with basic writing skills • A few great projects, a number of awful ones

  17. Solutions, 4 • Smaller, more focused tasks, more tightly related to needs in other modules • Better balance between learner autonomy and teacher control • More time on finding, reading and critical analysis of specific journal articles • Final project: write up a technical report from lab work – core skill, reinforces links with other modules

  18. Next iteration of module • Portfolio – 40%; fewer tasks, heavier weighting, tighter deadlines • Critical analysis of journal article – 15%; less choice, more focused guidance • Technical lab report – 30%; more relevant, less choice, lower weighting • Oral presentation – 15%; more relevant, smaller group, lower weighting

  19. Lessons learned • Module develops/improves with greater understanding of students’ abilities and needs • Fewer goals, clearly linked, more thoroughly taught and practiced • Better balance between teacher directive and student choice • Collaboration between discipline school and central learning development unit • shared module design and delivery can be effective

  20. Kal Winston, Study Skills Centre, Bangor Universityk.winston@bangor.ac.uk

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