Search

At the Department of Electrical and Computer Engineering and the School of Biomedical Engineering at the University of British Columbia (UBC) a system of providing and refining time estimates for student completion of homework assignments has been introduced in two integrated second-year Engineering and Math courses. Particular attention has been given to individual homework questions. In this paper findings to date are presented after two offerings of the courses in which this system was implemented. By using student feedback from the first offering to adjust instructor time estimates, instructors were able to obtain time estimates accurate to within 5 minutes of student reported averages for 77% of ELEC211 and 64% of BMEG 220 questions. Student perception of the usefulness of time estimates was generally positive, ranging from 35% to 64% of students reporting the initiative to be either ‘useful’ or ‘very useful’ over 3 years of data. Examples drawn from both courses will be discussed to demonstrate how the collected data is being used to identify areas of further improvement to assignment questions and course structure.

PurposeStudents in flipped classrooms are challenged to orchestrate an increasingly heterogeneous collection of learning objects, including audiovisual materials as well as traditional learning objects, such as textbooks and syllabi. This study aims to examine students' information practices interacting with and synthesizing across learning objects, technologies and people in flipped classrooms.Design/methodology/approachThis grounded theory study explores the information practices of 12 undergraduate engineering students as they learned in two flipped classrooms. An artifact walkthrough was used to elicit descriptions of how students conceptualize and work around interoperability problems between the diverse and distributed learning objects by weaving them together into information tapestries.FindingsStudents maintained a notebook as an information tapestry, weaving fragmented information snippets from the available learning objects, including, but not limited to, instructional videos and textbooks. Students also connected with peers on Facebook, a back-channel that allowed them to sidestep the academic honesty policy of the course discussion forum, when collaborating on homework assignments.Originality/valueThe importance of the interoperability of tools with elements of students' information space and the significance of designing for existing information practices are two outcomes of the grounded theory approach. Design implications for educational technology including the weaving of mixed media and the establishment of spaces for student-to-student interaction are also discussed.

WeBWorK online homework usage data for a second-year, 130-student mechanical engineering course was analyzed using latent profile analysis (LPA) to identify student usage patterns and their relation to tests/exams grades. Ten WeBWorK usage variables were used by LPA to identify three distinct student sub-groups having particular usage patterns. The resulting three sub-groups were found to have statistically significant differences in tests/exam grades. Lower grades corresponded to fewer WeBWorK sessions and questions attempted, with a higher number of attempts and questions attempted per session; lower grades also corresponded to lower collaboration metrics and later first submissions of correct answers. These results might be used by instructors to inform and encourage online homework usage practices that are related to higher grades.

Biomechanical models of the oropharynx facilitate the study of speech function by providing information that cannot be directly derived from imaging data, such as internal muscle forces and muscle activation patterns. Such models, when constructed and simulated based on anatomy and motion captured from individual speakers, enable the exploration of inter-subject variability of speech biomechanics. These models also allow one to answer questions, such as whether speakers produce similar sounds using essentially the same motor patterns with subtle differences, or vastly different motor equivalent patterns. Following this direction, this study uses speaker-specific modeling tools to investigate the muscle activation variability in two simple speech tasks that move the tongue forward (/ə-ɡis/) vs backward (/ə-suk/). Three dimensional tagged magnetic resonance imaging data were used to inversely drive the biomechanical models in four English speakers. Results show that the genioglossus is the workhorse muscle of the tongue, with activity levels of 10% in different subdivisions at different times. Jaw and hyoid positioners (inferior pterygoid and digastric) also show high activation during specific phonemes. Other muscles may be more involved in fine tuning the shapes. For example, slightly more activation of the anterior portion of the transverse is found during apical than laminal /s/, which would protrude the tongue tip to a greater extent for the apical /s/.

In this paper the planning, implementation, and analysis of active learning techniques introduced into a new integrated course designed for second-year Biomedical Engineering students at the University of British Columbia are presented. The course included foundation material on circuit analysis, electromagnetics, and vector calculus. The course was delivered using a blended learning format, incorporating video content, traditional lecture time, and team based in-class problem solving. In general the problem solving activities were well received, but several adjustments were necessary during the term to optimize the effectiveness of the team-based activities. Student feedback and course outcomes are presented and discussed in the paper.

Online homework systems provide immediate feedback to students, enhancing student learning. However, paid online homework from textbook publishers or other sources systems can be costly and also raise concerns about student data privacy. WeBWorK is an open-source online homework system that can be setup on local servers, is free to students and has been in use since its development in the mid-1990s. Previous to this work around 200 engineering problems were openly shared on the WeBWorK platform, limiting opportunity for adoption. In order to address this, we have developed, deployed, and evaluated nearly 1000 new engineering problems across a wide range of engineering topics at the second-year level. Student perceptions of WeBWorK have been evaluated using surveys at the start and end of courses where it is deployed. These surveys indicate that students generally prefer the WeBWorK system to other online homework systems they have used. Surveys also indicate that students were generally motivated to both attempt and complete all assigned problems that contributed to their grade, and believed WeBWorK enhanced their learning. The creation of error-free WeBWorK questions was difficult, however the hope is that the ability to re-use and share these questions ensures they provide a higher value over the long term than paper-based homework problems.

Video is an increasingly popular medium for education. Motivated by the problem of video as a one-way medium, this paper investigates the ways in which learners’ active interaction with video materials contributes to active learning. In this study, we examine active viewing behaviors, specifically seeking and highlighting within videos, which may suggest greater levels of participation and learning. We deployed a system designed for active viewing to an undergraduate class for a semester. The analysis of online activity traces and interview data provided novel findings on video highlighting behavior in educational contexts.

Video-based learning is most effective when students are engaged with video content; however, the literature has yet to identify students' viewing behaviors and ground them in theory. This paper addresses this need by introducing a framework of active viewing, which is situated in an established model of active learning to describe students' behaviors while learning from video. We conducted a field study with 460 undergraduates in an Applied Science course using a video player designed for active viewing to evaluate how students engage in passive and active video-based learning. The concept of active viewing, and the role of interactive, constructive, active, and passive behaviors in video-based learning, can be implemented in the design and evaluation of video players.

Electromagnetics and vector calculus are taught as an integrated course in the Electrical Engineering program at UBC. In this paper, the course structure is described, and unique features are highlighted.A key goal of the course is to help students develop problem solving skills. To assist students in building these skills, a blended classroom approach has been adopted to allow an increase in discussion and problem solving activities in the classroom. Results of student assessment and a summary of student feedback on the teaching technologies and activities incorporated into the course are reported.

As videos are gaining popularity in flipped and blended Engineering classrooms, there is an increasing need to track and understand students’ use of the videos, in order to identify evidence-based practices matched to the emerging trends in video and video annotation tools. We explore students’ surveyresponses, follow-up interviews, and log data from their interaction with common video platforms as well as, ViDeX, a new experimental video annotation tool, to evaluate how, when and why students watch, rewatch, and annotate videos in two large introductory Engineering courses, with flipped, and blended formats. Our findings show that students watch thevideos with the instructors’ intended use in mind, and plan their review process accordingly. In the flipped classroom, most students summarized the short preclass screencasts in their personal notes to minimize the need to re-watch the videos before the exam. In contrast, students in the blended classroom reexamined the long tutorial videos mostly to redo the problems before the midterm and final exams. Bookmarking seemed to be useful for locating those problems of interest. Since the problems required drawings and computations, paper annotation was more beneficial than a dedicated video annotation platform.

Learning with online video is pervasive in higher education. Recent research has explored the importance of student engagement when learning with video in online and blended courses. However, little is known about students' goals and intents when engaging with video. Furthermore, there is limited empirical evidence on the impact of learning context on engagement with video, which limits our understanding of how students learn from video. To address this gap, we identify a set of engagement goals for learning with video, and study associated student activity in relation to learning context (course week, exam, and rewatch). In Study 1, we conducted a survey (n = 116) that maps students' video viewing activities to their engagement goals and intents. We identified a variety of engagement goals, specifically Reflect, Flag, Remember, Clarify, Skim, Search, Orient, and Take a break. In Study 2, we analyzed clickstream data generated by 387 students enrolled in three semester-long courses. We examined the impact of learning context on students’ engagement with video. A multilevel model showed different patterns for online and blended courses. Students in the online course showed much more strategic and adaptive use of video. As the semester progressed, students in the online courses performed fewer Reflect and Search. During exam weeks and when rewatching videos, online students performed more Search within the video. The only trend that was found for blended learning students was an increase in Skim with course week. These findings have implications for video players that adapt to context, such as helping students easily locate important in-video information during the exam week or when rewatching previously watched videos.

Biomechanical models of the oropharynx are beneficial to treatment planning of speech impediments by providing valuable insight into the speech function such as motor control. In this paper, we develop a subject-specific model of the oropharynx and investigate its utility in speech production. Our approach adapts a generic tongue-jaw-hyoid model (Stavness et al. 2011) to fit and track dynamic volumetric MRI data of a normal speaker, subsequently coupled to a source-filter based acoustic synthesizer. We demonstrate our model’s ability to track tongue tissue motion, simulate plausible muscle activation patterns, as well as generate acoustic results that have comparable spectral features to the associated recorded audio. Finally, we propose a method to adjust the spatial resolution of our subject-specific tongue model to match the fidelity level of our MRI data and speech synthesizer. Our findings suggest that a higher resolution tongue model – using similar muscle fibre definition – does not show a significant improvement in acoustic performance, for our speech utterance and at this level of fidelity; however we believe that our approach enables further refinements of the muscle fibres suitable for studying longer speech sequences and finer muscle innervation using higher resolution dynamic data.

We describe our approach to construct FRANK: a Functional Reference ANatomical Knowledge (FRANK) template of the head and neck. FRANK consists of a collection of anatomical components made of finite element models (FEM), rigid-bodies, spring-like structures, and various muscle types, all wrapped by an airtight parametrically controlled geometric covering. Its muscles can be activated to mimic complex actions such as swallowing, chewing, and speech, and its modular design allows for components to be replaced and tailored to target-specific applications. The underlying biomechanical modeling toolkit, ArtiSynth, uses a hybrid finite-element and multibody technique that is essential in allowing simulation of such processes within reasonable computation times. We also describe common challenges and various approaches to building hybrid models, such as FRANK, enabling the combination of organs into a unified framework. When combined with inverse modeling techniques, these hybrid models can be applied to a wide variety of applications, including modeling of function. We demonstrate some applications of FRANK, including swallowing, mastication, speech, and patient-specific anatomical modeling.

Static magnetic resonance imaging partially resolves soft tissue details of the oropharynx, which are crucial in swallowing and speech studies. However, delineation of tongue tissue remains a challenge due to the lack of definitive boundary features. In this article, we propose a minimally interactive inter-subject mesh-to-image registration scheme to tackle 3D segmentation of the human tongue from MRI volumes. A tongue surface-mesh is first initialised using an exemplar expert-delineated template, which is then refined based on local intensity similarities between the source and target volumes. A shape-matching technique [Gilles B, Pai D. 2008. Fast musculoskeletal registration based on shape matching. Paper presented at: MICCAI 2008. Proceedings of the 11th International Conference on Medical Image Computing and Computer Assisted Intervention; New York, NY, USA] is applied for regularising the deformation. We enable effective minimal user interaction by incorporating additional boundary labels in areas ...

In this work, we develop a 3D subject-specific biomechanical model of the oropharynx in order to investigate and simulate speech production. Our muscle-activated model is generated based on the subject-specific anatomy captured from dynamic volumetric cine-MRI data. Our model includes an air-tight deformable airway that enables speech synthesis. We simulate our model based on actual tissue motion tracked from the tongue during speech production, which we extract from the tagged-MRI data. We quantitatively validate our model on MRI data achieving an average target point tracking error of 1.15mm ± 0.632, and an acoustic formant frequency estimation error of 6.01% ± 4.92%.

We present a three dimensional (3D) biomechanical swallowing model of the oral, pharyngeal and laryngeal (OPAL) muscles and structures. Such modeling may aid in predicting functional outcomes in swallowing disorder (i.e. dysphagia) treatment and could significantly reduce therapy time. Our physics-based model captures the OPAL anatomical geometries and kinematics from 2D animations constructed from video-fluoroscopic (VF) evaluations of real patient swallowing events using the Modified Barium Swallow Impairment Profile (MBSImP™©) protocol. We investigate the upper airway dynamics with these clinically accurate kinematics and geometries. We use smoothed particle hydrodynamics (SPH) modeling of water-like and nectar-like fluid boluses, simulated within an airway-skin mesh that encompasses our modeled 3D structures and follows the model's dynamics. We demonstrate that our model can simulate a bolus in a manner consistent with clinical data, and can robustly handle fluid with different viscosity incorporating a wide range of moving boundary conditions.

Subject-Specific biomechanical modelling of the human tongue is beneficial for investigating the inter-subject variability in the physiology of the speech, chewing and swallowing. Delineation of the tongue tissue from MRI is essential for modelling, but still remains a challenge due to the lack of definitive boundary features. In this paper, we propose a minimally interactive inter-subject mesh-to-image registration scheme to tackle 3D segmentation of the tongue from MR volumes. An exemplar expert-delineated template is deformed to match the target volume, constrained based on a shape matching regularization technique. We enable effective minimal user interaction by incorporating additional boundary labels in areas where automatic segmentation is deemed inadequate. We validate our method on 12 normal-subjects. Results indicate an average dice overlap of 0.904 with the ground truth, achieved within 3 min of the expert interaction.