Consistency in Assessment of Pre-Engineering Skills
Notice bibliographique
Résumé
Abstract Consistency in Assessment of Pre-Engineering SkillsAssessment tools are often used in a predictive way to gauge the overall skills of first-yearengineering students as they begin their engineering education. They are also useful in settinginterventions in terms of tutorials, as well as providing self- improvement motivation for thestudents who achieve scores that are not consistent with earlier high school performance.Previous research has demonstrated that the academic averages obtained in high school, may notnecessarily reflect the skill level (competency) of the students entering first-year, especially inmathematics. However, a longitudinal study over more than ten years has also indicated that theaverages from the math advisory and engineering assessment (Force Concept Inventory) examsdid not show a statistically significant decline during that time period. In this study, both themath and engineering assessment results were further analyzed on a per question basis todetermine whether or not there were any observable trends in the student responses.The results for math assessment exams, taken over thirteen years, indicated that the averageperformance on each question every year is statistically very consistent. The questions that themajority of the students got right each year, and those that the majority got wrong each yearshowed very little variation in the standard deviation (typically < 5%), which was used as themeasure in variability of the mean. The results were further analyzed by categorizing thequestions according to three classifications: algebra, trigonometry and geometry. Typically, thequestions with the best overall performance were simple algebra questions, and the questionswith the worst overall performance involved trigonometric concepts. Moreover, as thecomplexity of the algebra questions increased, the success rate on those questions diminished asexpected. Both assessment exams were time limited and students were not allowed to usecalculators. In the high school curriculum in our region, students use calculators regularly in theirhigh school math courses. As a result, their inherent competency in trigonometric functions islacking, as the average scores (typically less than 30%) on these questions would indicate.Engineering assessment (Force Concept Inventory) exam results collected over a slightly shorterduration (six years) were also analyzed. The same trends in student responses were observed, butin this case the results were somewhat less striking than the results obtained from the mathassessment. It is clear, however, that there is a consistency on the success rate for individualexam questions that test both math and engineering concepts. These results support the anecdotalcontention that students collectively have competency in certain areas (algebra) but lackcompetency in others (trigonometry). It further demonstrates that students often come into first-year engineering with common misconceptions and common math deficiencies.The results from this study are useful from several perspectives. They can provide a focus forinterventions that might address both competency and misconceptions. Secondly, the consistencyand repeatability of this data may provide an impetus to work with K-12 educators to addressthese issues before the students reach university. The consistency of this data also implies thatpre-engineering skills are somewhat predictable from year to year.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,027 | 0,109 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».