Administating Engineering Student Project in a Research Laboratory
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The document outlines the structure and significance of student projects in Indian engineering curricula, emphasizing their role in bridging the gap between academic education and industry requirements. It defines project success through a model that predicts outcomes based on various essential and non-essential parameters derived from previous student projects. The findings indicate the importance of effective project management and guidance in enhancing students' educational experiences and their future career opportunities.
Administating Engineering Student Project in a Research Laboratory
- 1. Student Project Administration at a Research Laboratory SIBIRCON 2010 Sunil Kumar Kopparapu (Virtual) SunilKumar.Kopparapu@TCS.COM Speech and Natural Language Processing Group TCS Innovation Labs - Mumbai Yantra Park, Thane (West), Maharastra, INDIA. 13 July 2010 c Tata Consultancy Services Limited 2010 – p.1/18
- 2. Overview Student Project (Why?, What?, How?) Measuring successful project (Why?, How?) Parameters associated with student project Model to predict project success Experimental Results Conclusions c Tata Consultancy Services Limited 2010 – p.2/18
- 3. Student Project - What? Student projects are an essential part of a four year graduate course in most universities world wide In most Indian universities the project in an Engineering discipline is mandatory and is spread over a period of two semesters (part time) for a graduate course (8 - 10 hours a week) for a post graduate course it is spread over a period of one semester full time (30 hours a week) At the end of the project duration the student is assessed by a panel of examiners and awarded a suitable grade. c Tata Consultancy Services Limited 2010 – p.3/18
- 4. Student Project - Why? In the Indian scenario the basic aim of such a project is to give necessary industrial exposure to the graduating students exposure is deemed necessary in order to bridge the transition gap between university education and a professional job the project benefits both the student and the industry is a welcome aspect of the education process Very often the project plays an important role in what job offers a student gets ... c Tata Consultancy Services Limited 2010 – p.4/18
- 5. Student Project - How? Ideally, student adviser is a full time member of the research staff at the Laboratory students spend a sizable amount of time discussing the project plan and related issues with the adviser 15 % of time is spent to invoke continued interest in the project, 35 % time spent in day to day discussions (planning and evaluating results) 20 % in evaluating project reports from the intellectual property rights (IPR) angle c Tata Consultancy Services Limited 2010 – p.5/18
- 6. Student Project - How? 5 % of time in planning the infrastructure and making available the necessary computing and logistics facilities remaining time goes in keeping oneself updated • about the progress elsewhere in the research community • finding possible extensions to the project plan to make the project output more useful and current c Tata Consultancy Services Limited 2010 – p.6/18
- 7. Successful Project - A Definition Success of a student project is difficult to define because especially when it is setup in a research environment, the probable outcome is difficult to predict A successful project is defined the project is brought to a logical conclusion gives the adviser a sense of satisfaction makes the student motivated to continue similar studies in the future fetches good grades c Tata Consultancy Services Limited 2010 – p.7/18
- 8. Why Measure a Project Several Reasons students get better grades students are inclined to work in research areas advisers time spent has tangible output More importantly, Management of the research lab is assured that the time of the adviser is well spent! c Tata Consultancy Services Limited 2010 – p.8/18
- 9. Features that measure success Features identified based on statistics Features derived from projects undertaken by 29 students from 6 different colleges over a 25 month period Features categorized as essential and non-essential in terms of driving a project towards success c Tata Consultancy Services Limited 2010 – p.9/18
- 10. Features that measure success Essential Clarity of problem definition Team Availability: full time or part time Team Size: defined as small (< 3) else large. Project Background: details available at the start Team cooperation: assignment division Motivation: excitement within the team Adviser Time: extent of guidance on an ongoing basis Team composition: Boys or Girls or mixed. c Tata Consultancy Services Limited 2010 – p.10/18
- 11. Features that measure success Prerequisites: required for the project Interaction: with other members of the laboratory Targets being set: short goals so focused results non-essential Skill set: of the team depending on the project. For example programming skills for an implementation project. Data availability if the project needs it. c Tata Consultancy Services Limited 2010 – p.11/18
- 12. Reference Data used for Modeling No Coll # Studts Course FT/PT Prfm (30) 1 Coll A 5 Grad PT 14.2 2 Coll B 6 Grad FT: 18.8 3 Coll C 3 Grad PT 25 5 Post Grad FT 29 4 Coll D 4 Grad PT 11 5 Coll E 3 Grad PT 23 6 Coll F 1 Grad PT 11 7 Coll G 1 Grad PT 11 Overall 6 29 18.58 c Tata Consultancy Services Limited 2010 – p.12/18
- 13. Features from Reference Data Feature Weights c1 Problem Definition 0.13 c2 Full time and dedicated team 0.11 c3 Small team (size 2/3) 0.08 c4 Background of the project clear 0.08 c5 Team cooperation 0.08 c6 Team excitement 0.05 c7 Good and continued guidance 0.11 c8 Girl team 0.03 c9 Students have prerequisites required 0.05 ca Lab Interaction 0.09 cb Short goals 0.12 cc Programming skills 0.07 c Tata Consultancy Services Limited 2010 – p.13/18
- 14. Model to Predict Project Success Based on the reference data, a linear model for a successful project was derived as f(c) = 0.13c1 + 0.11c2 + 0.08c3 + 0.08c4 + 0.08c5 + 0.05c6 + 0.11c7 + 0.03c8 + 0.05c9 + 0.09ca + 0.12cb + 0.07cc 0 ≤ f(c) ≤ 5.0 Failure 5.1 ≤ f(c) ≤ 6.0 Moderate Success 6.1 ≤ f(c) ≤ 7.0 Success 7.1 ≤ f(c) ≤ 9.0 Good Success 9.1 ≤ f(c) ≤ 10.0 Super Success c Tata Consultancy Services Limited 2010 – p.14/18
- 15. Need for Modeling accessing the outcome of a project is desirable it is crucial because the overheads associated with a student project on the laboratory is quite large in terms of resource usage and research staff time a decision can be taken • A student project predicted in the category Success, Good Success, Super Success are the projects that can be initiated • the rest can be shelved until the right combination of the project and the students is found c Tata Consultancy Services Limited 2010 – p.15/18
- 16. Experimental Results Prediction of the outcome of in progress projects Student Project Predict (Jul) Observed (Oct) Online to Offline Success Super Success Online script recognition Success Good Success Staff Management (Team 1) Mod Success Good Success Staff Management (Team 2) Success Good Success It can be observed that predictive estimate (Jul) have been lower than what they stood in Oct, suggests the model is pessimistic; fine tuning of parameters required to capture a more real modelc Tata Consultancy Services Limited 2010 – p.16/18
- 17. Conclusions Student projects are essential part of engineering curriculum in Indian Universities Research labs spend resources to undertake these projects Ability to predict the success of a project helps research laboratories We derived a model to predict the success of a project Validated the model on several projects to measure the success of a student project c Tata Consultancy Services Limited 2010 – p.17/18
- 18. Thank You Queries? Comments Suggestions? SunilKumar.Kopparapu@TCS.Com TCS Innovation Lab - Mumbai Tata Consultancy Services Limited Yantra Park, Thane (West), India. c Tata Consultancy Services Limited 2010 – p.18/18