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Record W2617883294 · doi:10.18260/1-2--8034

Using Robus In Electrical And Computer Engineering Education

2024· article· en· W2617883294 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsUniversité de Sherbrooke
FundersUniversité de Sherbrooke
KeywordsMicroprocessorRobotRoboticsTeamworkComputer scienceCurriculumEngineering educationEngineering managementMultimediaEngineeringArtificial intelligenceSoftware engineeringElectrical engineeringEmbedded systemPedagogyPsychologyManagement

Abstract

fetched live from OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 2220 Using ROBUS in Electrical and Computer Engineering Education François Michaud, Mario Lucas, Gérard Lachiver, André Clavet, Jean-Marie Dirand, Noël Boutin, Philippe Mabilleau, Jacques Descôteaux Université de Sherbrooke (Québec Canada) Abstract ROBUS (ROBot University of Sherbrooke) is an autonomous mobile robot designed to facilitate interdisciplinary engineering design in Electrical Engineering (EE) and Computer Engineering (CE). Its primary purpose is to serve as an integrated platform for a project called INGÉNIUS that introduces electrical and computer engineering simultaneously to a large group of first-year undergraduate students registered in these two distinct programs. Divided in thirty-five teams of six or seven, these students are being initiated to various aspects of electrical and computer engineering such as electric circuits, electronics, sensors and actuators, logic circuits and CPLD, microprocessors, real-time C programming, robotics, technical drawing and communication. This way, ROBUS gives hands-on technical and teamwork experiences early in the curriculum. The robot is used in six different courses, and an interdisciplinary team of professors also work together to coordinate these activities. At the end of the second semester, teams participate in a robot competition where the objective is to design an entertainment robot for children with learning disorders. For fourth-year students in EE and CE, ROBUS is used in more advanced undergraduate courses such as Microprocessor Interfaces, Real-Time Systems, Robotics Projects and also in one graduate course on Artificial Intelligence. The projects done in these courses are oriented toward giving more advanced capabilities to ROBUS, help developed complete autonomous robots and to teach specific concepts. This paper gives a description of ROBUS and how it is used in these activities. I. Introduction The Department of Electrical and Computer Engineering at the Université de Sherbrooke offers two distinct bachelor engineering degrees, one in Electrical Engineering and one in Computer Engineering (which has been initiated six years ago). Even though both programs share some activities and that students are placed in an environment that involves electrical and software considerations, students are still having difficulties integrating and applying the engineering knowledge and skills that they learn. To avoid this problem, we thought that more could be done to develop this ability early in the curricula. We also wanted to put students in situations closer to the reality of the profession by making them work on projects that involve multidisciplinary considerations, design and analysis abilities, autonomous learning, teamwork and communication skills.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.270
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations11
Published2024
Admission routes3
Has abstractyes

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