Browsing by Author "Marasco, Emily"

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    Advantages of making a SELFIE - Self Evaluation Learning Framework in Exams
    (2015-05-12) Marasco, Emily; Smith, Michael; Gorobets, Mila
    A steep learning curve is introduced by early emphasis on tools and techniques during science and engineering courses needed for hands-on, practical laboratory experiences. Associated discrepancies between a student’s perceived theoretical background and the practical application of that background knowledge leads to different study behaviours during quizzes and exams: 1. Those who have correctly taken into account the complexity level of each course component. 2. Those who believe they have taken the complexity changes into account; but need to study and seek mentoring because they have not. 3. Those who believe they are not coping with the complexity changes but are in fact doing well; perhaps these students should be moving some study time onto other course exams. To assist students in more accurately determining into which category they currently fall, we introduced a Self-Evaluation Learning Framework for use In Exams and quizzes – SELFIE. Following a decade of using an ad-hoc SELFIE and the increased interest in the advantages of self-assessment at the university level [1, 2], we have formalized the approach [3]. We present results from student self-analysis during midterm and final exams. We detail one approach to addressing student concerns about their self-evaluation – a “Make up your own question and answer it” question during final exams. Designed to provide an opportunity to boost marks for students interested in the course material but struggling, the Make-Your-Own Question has proved popular for students who want to be remembered by the instructor and get a good job or internship reference.
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    A collaborative autoethnographic analysis of industry-academia collaboration for software engineering education development
    (Canadian Engineering Education Association, 2022-06) Marasco, Emily; Barcomb, Ann; Dwomoh, Gloria; Eguia, Daniel; Jaffary, Abbas; Johnson, Garth; Leonard, Lance; Shupe, Ryan
    As engineering educators seek to prepare students for future careers, it can be challenging to keep course materials current with industry practices and knowledge. Students also often experience a disconnect between their studies and perceived relevance to future industry roles. This study examines the potential impact of an industry-academia collaboration on the development and improvement of software engineering education while addressing these issues. A collaborative autoethnographic approach is used to concurrently analyze the experiences of both industry and academic participants in the collaboration. Common themes across the collected personal reflections show that varied benefits were experienced by all stakeholders while contributing to an improved student experience.
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    Development of an IoT System to Gather, Assess, and Improve Cyber-Physical Interaction Data
    (2023-06) Long, Jason; Behjat, Laleh; Brennan, Bob; Bartley, Norm; Marasco, Emily
    A sensor network consisting of small circuits that can be attached to physical equipment in a classroom environment was designed, manufactured, programmed, and tested. Each sensor measures human interaction with the equipment to which it is attached based on motion and reports the data wirelessly to a central Hub computer. All sensor operation is autonomous and requires no direct user-input. The sensors optionally and automatically pair with users through an associated user-worn sensor. The sensor network operates continuously over a long period of time with zero maintenance or operator intervention. The intention of this system is to collect data in a classroom to identify what equipment students use regularly. With this information, educators can make informed decisions about the impact that various resources have. To prove the functionality of the technology developed, a study was done at a fitness center where the sensors were attached to exercise machines. This was a comparable environment to a classroom as it involves consistent human-equipment interaction and was more readily accessible for this research due to ethics involving young students in research along with access restrictions due to COVID-19. The work carefully details the hardware and firmware development of the sensors as they are intended to be commercial-grade yet low cost for mass production. Thirty-five Equipment Sensors and fifteen User Sensors were fabricated and installed in the fitness facility for a two-week period and produced over 30,000 data points. Using redundant sensors on each equipment enabled comparison of the technical performance without having to directly involve gym participants. This gave the benefit of an authentic testing environment where participants would not change their behavior due to the study. The sensor data was used to assess the sensor’s technical performance. The Equipment Sensors provided reliable indication of equipment usage. The User Sensor portion of the study was limited as participation was voluntary and only passively advertised. Recommendations are provided on how to improve the sensor network and use it for future educational research in the classroom.