Teaching Teamwork: Electronics Instruction in a Collaborative Environment

Horwitz, Paul; Davier, Alina von; Chamberlain, Jon; Koon, Al; Andrews, Jessica J.; McIntyre, Cynthia

doi:10.1080/10668926.2016.1275886

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…For the group task, called the Three-Resistor Activity (Horwitz et al, 2017), students worked in groups of three, with each student on a separate computer that ran a simulation of an electronic circuit. Each student's simulation in a team was connected to form a series circuit.…”

Section: Taskmentioning

confidence: 99%

Towards automatic annotation of collaborative problem‐solving skills in technology‐enhanced environments

Flor

Andrews‐Todd

2022

Computer Assisted Learning

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Background Collaborative problem solving (CPS) is important for success in the 21st century, especially for teamwork and communication in technology‐enhanced environments. Measurement of CPS skills has emerged as an essential aspect in educational assessment. Modern research in CPS relies on theory‐driven measurements that are usually carried out as manual annotations over recorded logs of collaborative activities. However, manual annotation has limited scalability and is not conductive towards CPS assessments at scale. Objective We explore possibilities for automated annotation of actions in collaborative‐teams, especially chat messages. We evaluate two approaches that employ machine learning for automated classification of CPS events. Method Data were collected from engineering, physics and electronics students' participation in a simulation‐based task on electronics concepts, in which participants communicated via text‐chat messages. All task activities were logged and time stamped. Data have been manually classified for the CPS skills, using an ontology that includes both social and cognitive dimensions. In this article, we describe computational linguistic methods for automatically classifying the CPS skills from logged data, with a view towards automating CPS assessments. Results We applied two machine learning methods to our data. A Naïve Bayes classifier has been previously used in CPS research, but it is only moderately successful on our data. We also present a k‐nearest‐neighbours (kNN) classifier that uses distributional semantic models for measuring text similarity. This classifier shows strong agreement between automated and human annotations. The study also demonstrates that automatic spelling correction and slang normalization of chat texts are useful for accurate automated annotation. Implications Our results suggest that a kNN classifier can be very effective for accurate annotation of CPS events. It achieves reasonably strong results even when trained on only half of the available data. This shows a promise towards reduction of manual data annotation for CPS measurement.

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Section: Taskmentioning

confidence: 99%

Towards automatic annotation of collaborative problem‐solving skills in technology‐enhanced environments

Flor

Andrews‐Todd

2022

Computer Assisted Learning

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“…The BCU teachers indicated that they had encouraged students to communicate via the MOODLE platform chat option. In their opinion, it was similar to email as a means of communication, but they could control the resolution of doubts in a simpler and more effective way, as the finding of other studies have also shown [ 71 ]. Furthermore, MCU teachers indicated that they had promoted the use of email because it allowed them to better reconcile their teaching activity with family life.…”

Section: Resultsmentioning

confidence: 99%

“…However, the use of web tools (Skype, Microsoft Teams …) increased when their use was necessary for the explanation of practical concepts. In addition, specific differences were detected according to the preferences of each teacher, which led to the promotion of the use of one or another communication channel [ 71 ].…”

Section: Discussionmentioning

confidence: 99%

The Outbreak of the COVID-19 Pandemic and its Social Impact on Education: Were Engineering Teachers Ready to Teach Online?

Revilla‐Cuesta

Skaf

Varona

et al. 2021

IJERPH

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The major impacts of the COVID-19 pandemic are still affecting all social dimensions. Its specific impact on education is extensive and quite evident in the adaptation from Face-to-Face (F2F) teaching to online methodologies throughout the first wave of the pandemic and the strict rules on lockdown. As lesson formats changed radically, the relevance of evaluating student on-line learning processes in university degrees throughout this period became clear. For this purpose, the perceptions of engineering students towards five specific course units forming part of engineering degree courses at the University of Burgos, Spain, were evaluated to assess the quality of the online teaching they received. Comparisons were also drawn with their perceptions of the F2F teaching of the course units prior to the outbreak of the pandemic. According to the students’ perceptions, the teachers possessed the technical knowledge, the social skills, and the personal capabilities (empathy and understanding of the at times troubled situation of each student) for a very abrupt adaptation of their courses to an online methodology. The shortcomings of the online teaching were related to its particularities and each teacher’s personality traits. Overall, engineering teachers appeared well prepared for a situation of these characteristics and, if similar online teaching scenarios were ever repeated, the quality of engineering teaching appears to be guaranteed.

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“…Ante esta situación, fue necesario emplear estrategias de trabajo colaborativo, las mismas que permitieron un interaprendizaje, observando que el proceso de enseñanza de los pares tuvo mayor eficacia, en términos de tiempo de aprendizaje, además de generar un clima agradable y motivador entre ellos, en un espacio virtual por supuesto. Esto es explicable en la naturaleza socializadora del humano y en la generación de conocimiento a partir del mismo (Getha-Eby et al, 2014;Ercan & Ural, 2016;Salazar, 2018) adicionando al aprendizaje individual como resultado del proceso grupal (Kaye, 1992;Horwitz et al, 2017;Cui et al, 2020). Este nuevo entorno de socialización continuada en las fases de instrucción académica brinda nuevos horizontes a los docentes, quienes no solamente se reinventan sobre la marcha, sino que distinguen procesos de socialización que favorecen las habilidades de manejo de herramientas que conducen hacia metodologías que facilitan la metacognición.…”

Section: Resultados A) Análisis De Los Componentes Evaluados En La Resolución De Problemas De Figuras Geométricas Bidimensionalesunclassified

Software GeoGebra en la mejora de capacidades resolutivas de problemas de figuras geométricas bidimensionales en universitarios

Melgar

Osores

Tarazona

et al. 2021

PyR

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El objetivo fue evaluar el efecto de la aplicación del software GeoGebra en las habilidades de resolución de problemas de figuras geométricas bidimensionales en una muestra de 53 estudiantes universitarios distribuidos en dos grupos (control – experimental) evaluados en dos momentos: antes y despues de la intervención. Se emplearon pruebas paramétricas para comparación de pares relacionados e independientes y no paramétricas para comparar entre los niveles de clasificación. Los resultados evidenciaron que el grupo experimental post test fue el que mejor rendimiento presentó demostrándose que el uso del software GeoGebra mejoró las habilidades resolutivas de ese tipo de problemas matemáticos fomentandose el trabajo colaborativo, integración socio estudiantil y mejora del clima de clase. Se recomienda ampliar el uso de esta herramienta con otras aplicaciones que coayuven el proceso de enseñanza aprendizaje.

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Teaching Teamwork: Electronics Instruction in a Collaborative Environment

Cited by 7 publications

References 4 publications

Towards automatic annotation of collaborative problem‐solving skills in technology‐enhanced environments

Towards automatic annotation of collaborative problem‐solving skills in technology‐enhanced environments

The Outbreak of the COVID-19 Pandemic and its Social Impact on Education: Were Engineering Teachers Ready to Teach Online?

Software GeoGebra en la mejora de capacidades resolutivas de problemas de figuras geométricas bidimensionales en universitarios

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