]) mainly so that we can focus on the moreimportant Coverage metric. Only correlations are presented here – deeper statistical analyses onthe data is pending. Effects of gender, pre-course GPA and numerical course grade on Coverageare not explored. No attempt was made to determine directly the reason for the trends inCoverage (e.g. by surveying students), but this is planned for future studies.ConclusionsThe data presented in this paper on the extent of video viewing of pre-class videos (as measuredby the Coverage metric) in three flipped undergraduate engineering courses (numerical methodsfor engineers, fluid mechanics and engineering statics) with almost identical course structuresthat were taught by the same instructor, suggest the following
cognitive load during problem solving.Nonetheless, we plan several improvements to the experiment to remedy specific issuesencountered during this first round of data collection. The promise of eye gaze technology is thatwe can know, with very high resolution, exactly where the participant is looking on the computerscreen. So we should be able to tell whether a participant is looking at the figure, the problemstatement, or a particular equation while fixated on the worked-example video during theexperiment. However, because the participant frequently moves their head back and forth—looking at the computer screen, then their written work, and back—we are not confident that theeye gaze system calibration or pupil tracking is robust against those
-Gauthier, University of Puerto Rico, Mayaguez Campus Genock Portela is Associate Professor and former Associate Director in the Department of General En- gineering at the University of Puerto Rico, Mayaguez. He earned a Ph.D. degree in civil engineering at the University of Puerto Rico, Mayaguez (2004). Portela has primary research and teaching interests in structural mechanics, mostly oriented to bridge, earthquake, and wind engineering. In the General Engi- neering Department at UPRM, Portela serves as President of the Planning and Development Committee and member of the Engineering Mechanics Committee.Wadson C Phanord, University of Puerto Rico, Mayaguez. c American Society for Engineering
%, and88% for sections 1, 2, and 3, respectively) were Mechanical Engineering students. The threeinstructors of the different sections all had prior experience teaching dynamics within theFreeform framework. Each of the sections had common homework assignments, midterm exams,final exams, and course policies defined in the course syllabus. The three sections also shared acommon blog space for online collaboration and communication. However, each instructor hadthe freedom to use their own pedagogical discretion in planning class activities and assigningquizzes. During the second week of classes, the pre-test of the 11-item aDCI was administered ina pencil-and-paper format during class. The identical aDCI post-test was incorporated into thefinal exam
material that may have been prepared in previousyears, another investment of time and energy. These “energy bumps” become less severe as thesemester progresses and especially in subsequent years, but the additional upfront effort coulddiscourage some young faculty from implementing the new model. These concerns are partially,though not completely, alleviated by the new course structure proposed in the previousparagraph.Some tips for ease of implementation: 1. Plan ahead. The number one tip is to strategize and prepare in advance as much as possible. From choosing the software one feels more comfortable with to design the exams with, to having handouts prepared in advance (during previous semester or over the summer), to having
majorconceptual errors are drastically reduced by the end of the course and the majority of errors areminor execution and non-conceptual.Moving forward, there are plans to develop a macro for the spreadsheet that would generatetabular and graphical data for each student on their personal performance at three pointsthroughout the semester (following each exam). Students would get a breakdown of the specificmistakes made on all quizzes and exams as well as a pie chart similar to Figure 11 that presentsthe percentage of mistakes within the categories of Major Conceptual, Minor Execution, andNon-Conceptual Errors. The next step that would coordinate this personalized report would beto develop specific remediation exercises to support each type of error. For
user can solve equations of equilibrium using a built-in calculating facility. If the userhas written down an equation with one variable (always a linear equation in truss analysis), uponrequest the tutor can solve the equation for that variable. This eliminates the need to use acalculator. The user can substitute such a solved variable into another equation that has morethan one variable. But the tutor does not permit the simultaneous solution of multiple equationsfor multiple variables. This restriction on the solving capability promotes the practice of seekingto find an equation with a single variable, which can be determined and then used in subsequentequations. Such a practice of planning and organizing one’s work is often wise when
over plans and thought processes. I realizenobody will be holding our hand in the „real world‟, but for now we are still in training; nomember or my tam felt extremely confident about what we were turning in at the end.” Theseand other honest comments by the students will be extremely helpful for future students workingon the project.Students were concerned about the amount of time spent on all the assignments for the course,with 78% of the students admitting they worked more than 3 hours per week, while 22% saidthey spent 2-3 hours per week.Aware of the world comments:When asked if the students felt that participating in this project increased their awareness ofworld issues and global needs, the outcome was 83% yes and 17% no. “This
. James H. Block. New York: Holt, Rinehart and Winston, 1971.3. Keller, Fred Simmons, John Gilmour Sherman, and Carolina Martuscelli Bori. PSI, the Keller Plan Handbook: Essays on a personalized system of instruction. Menlo Park, Calif.: WA Benjamin, 1974.4. Onipede, O., and Warley, R., "Rethinking engineering exams to motivate students," 26th Annual Lilly Conference on College Teaching, Miami University, Oxford, OH, October 2007Appendix: Survey Questions1. I feel confident in taking future courses that require E MCH 211 as a pre-requisite.2. I think it is important to be able to solve problems correctly3. I feel that the grades I received in E MCH 211 with mastery exams was a fair evaluation of my understanding of that subject
understand its utility [11] - [14]. A recentreport showed that a large number of universities planned to build blended learningenvironments [15]. Previous meta-analysis studies have shown the benefits of blended learningfor student learning [11], [16], [17]. However, other researchers have argued that the effects ofblended learning on student learning should be examined based on a blended learningenvironment as a whole learning system, rather than separate blended learning techniques basedon causal effects of research intervention [4]. In this paper, we consider Freeform as a learningsystem that offered active and collaborative learning opportunities to students in and out of theclassroom.Jeong and Hmelo-Silver proposed seven computer supported
what to teach and how to organize assessment. The change to mastery-basedgrading has achieved the primary objective, but it has also engendered a culture shift of studentswho experience this system. Conversations about grading with students are more focused onauthentic learning issues than they were with the traditional system and students have shown thatthey understand and embrace the values associated with mastery-based grading.References[1] M. W. Durm, “An A is not an A is not an A: A history of grading,” Educ. Forum, vol. 57, no. 3, pp. 294–297, 1993.[2] A. Kohn. Punished by Rewards: The Trouble with Gold Stars, Incentive Plans, A’s, Praise, and other Bribes, Bridgewater, NJ: Replica Books, 1993.[3] K.D. Hjelmstad and A
, and encouraging internal motivation20. As wasshown in the cluster analysis, students from each cluster could demonstrate adaptive HSBs, andcases of adaptive HSBs were found involving each of the nine resources included in the analysis.Motivating students to make the best use of their study time through adaptive help seeking hasthe potential to positively impact student performance21, while still allowing students thefreedom to study according to their personal preferences. Our next steps in planning the future ofFreeform will draw on previous HSB publications in the Blended Learning space24,39,40 as weexplore how to facilitate a more positive and adaptive learning experience. Finally, in addition to enjoying the sheer number of resources