an online class. The implementation of the interventions may look different in each of those venues or20 have different levels of effectiveness because every classroom environment differs and faculty21 deployment of instructional practices varies. The strongest recommendation of the authors is to deploy a22 reflective process throughout implementation of some of the different teaching practices. This will allow23 for personal and professional growth in deploying the techniques while improving their use in their local24 teaching context over time.25 Introduction26 Statistics about Why Students Leave College and STEM Fields27 The current state of higher education is tragic. The U.S. Department of Education reported in 2015
post-activity reflection takes approximately 40-50 minutes to complete.Initial Implementation and Next StepsThis activity was completed with a class of 67 chemical engineering seniors in the Fall 2018academic term. During the activity, students seemed engaged with their groups, and each groupcompleted the tasks set before them successfully. The pre-class survey was completed by 66students, while the post-class survey was completed by all 67 students. The averaged results ofstudent self-evaluation of confidence in each area on an eight-point Likert scale (where 1 is leastconfident and 8 is most confident). In the initial run of the activity, data was collectedpredominantly to assess if students were appropriately engaging with and reflecting on
discouraging motivations are competitive classroom environments andgrades [14]. While grades are an evaluation of student learning inferred by the instructor,students’ grades have been interpreted by students as a measure of success and achievement.Students with lower performance or grades, therefore, become less motivated and doubt theirabilities to be successful in the engineering program. Other educational factors reported asdiscouraging to students’ motivation were time commitment on course tasks and the quality ofteaching with large effects for female than male students [14]. Although grades reflect students’competence and indicate growing opportunities, how students interpret the grades to impact theirmotivation and persistence in
suggested eight learning outcomes thatwould meet the ABET program criteria [2]. To determine which outcomes are currently beingtaught in the UO laboratory, the curricula from six different universities were analyzed using theeight Chemical Process Safety learning outcomes recommended by SAChE [3]. The results ofthat study showed that process safety is minimally covered in the UO laboratory, and that otheraspects of process safety are not covered even at the wider curriculum level.To create the necessary curricular change, a recent model suggests four different strategies canbe used independently or collectively to create change in higher education. These strategies are1. policy, 2. shared vision, 3. curriculum and pedagogy, and 4. reflective
). Follow- ing his Ph.D., Zhang worked in Enrique Iglesia’s group at the University of California, Berkeley as a postdoctoral researcher from 2013-2015. c American Society for Engineering Education, 2019Work in Progress: Improving critical thinking and technical understanding as measured in technical writing by means of in-depth oral discussion in a large laboratory class.Engineers are expected to be good at critical thinking, yet it is something that is difficult to teach anddifficult to measure. It is especially challenging to do so in a large class. Two common methods ofimproving critical thinking are through reflective writing and problem-based learning. Another commonelement that is often shown to help is
managers to ensure that programmes ofstudy throughout the HEI better reflect student needs and expectations and adhere to arecently revised institutional teaching and learning strategy. This review is also driven by arecognition that the student body has changed with traditional modes of teaching seeminglyoutdated and ineffective. For example, it has previously been suggested that one of thegreatest obstacles to overcome with respect to creating the right type of education forchemical engineers, does not arise from external drivers, but in recognising and responding tointernal factors – amounting to fundamental pedagogical shifts in learner behaviour andexpectation [1].Methodological approachOur approach taken to this review is principally a case
intensive course for our discipline, and the students satisfy this requirementby writing ten 500-word essays on a variety of design-related topics, including the ancillarytopics listed above. The student increase in understanding and incorporation of these ancillarytopics into their design is partially reflected in the upward-trending average score for the writingintensive assignments, which went from a mid-B (86) in the 2016 course offering to a high-B(89) or low-A (91) in the 2017 and 2018 course offerings.Figure 1. Enhanced Structure and Functionality of TAMUK Chemical Engineering CapstoneDesign ExperiencePerformance of Student Teams in Capstone DesignTable 1 presents some of the factors that may be unique to Hispanics or other
. Several innovative course elements andassignments are described in more detail below.Table 1. Course Topics and Assignments Question Course Topics Assignments What is chemical Chemical engineering Group project focused on engineering and what can coursework and applications chemical engineering I do with a degree in Career paths in chemical companies chemical engineering? engineering Personal reflection Guest speakers from industry, assignments on guest academia and government speakers How can I succeed in
also note that we did not assess student perceptions of techno-economic modeling. Researchsuggests that student perceptions are not reliable indicators of whether an intervention supportslearning [28]. However, we do note that students engaged deeply with the assignments, whichsuggests that students found them valuable. However, future studies can investigate specificaspects students found worthy to invest time. As a fairly authentic task, exploring how techno-economic modeling might support professional identity development would be of interest.We conclude with implications for other chemical engineering faculty by reflecting on classroomexperiences in this study. We have dived deeper in this challenge every year and students areengaged but
. Behaviors that are transcribed and coded have beendeemed likely behaviors while composing a technical report based upon literature search [6], [7].The ability for this method to capture the ability of a student to express certain behaviors in thecognitive writing process while also leaving room to evaluate activities that have not beenpreviously valued as important during the process allows for this portion of the study to build upquantitative and qualitative data. Groups of students who have taken ENGR 248 and groups ofstudents who have not will be graded on a rubric of cognitive writing processes to see whichbehaviors reflect previous dedicated technical communication training. Similarly, a students finalproduct can be assessed on a rubric of
, Solutioncompletion and Solution accuracy. Each item in the revised PROCESS consists of four scalinglevels ranging from 0 to 3 with zero being the minimum attainable score for each item. Anyidentification regarding group identity was removed prior to scoring and replaced with a project-assigned ID number to maintain privacy and to mask group membership from raters. All students’solutions were scored using the PROCESS rubric after the semester. Thus, PROCESS scores donot reflect or have an effect on students’ course grades.Raters’ scores for a subset of student solutions were analyzed to determine how consistently ratersmeasured student problem solving ability. Traditional statistical (Cohen’s kappa) and itemresponse measures (Rasch many facet model) of inter
- lished two books, ”Fundamentals of Chemical Engineering Thermodynamics” and ”Interpreting Diffuse Reflectance and Transmittance.” He has also published papers on effective use of simulation in engineer- ing, teaching design and engineering economics, and assessment of student learning.Dr. Laura P. Ford, University of Tulsa LAURA P. FORD is an Associate Professor of Chemical Engineering at the University of Tulsa. She teaches engineering science thermodynamics, mass transfer/separations, and chemical engineering senior labs. She is a co-advisor for TU’s student chapter of Engineers Without Borders USA. Her email address is laura-ford@utulsa.edu.Dr. Lucas James Landherr, Northeastern University Dr. Lucas Landherr is an
significant asdetermined using chi-squared tests (p < 0.05).Of the students responding to the end-of-quarter student evaluations of teaching, the number ofstudents reporting that they attended 80% or more of the lectures increased from about 74% inthe ’17 offering of the course to about 85% in the redesigned ’18 offering of the course, asshown in Figure 1B. Further, none of the students responding to the evaluation after theredesigned course reported attending less than 60% of the lectures. It must be noted that sinceattendance was self-reported and data was only available from the students completing thesurvey, these results may not reflect the actual attendance in lecture. Anecdotally, lectureattendance was observed to be better throughout the
reflect the desired number of groups, the number of laboratoryexperiments available, and the total number of available lab days. A second worksheet includes alist of generic placeholder values for student names. Replace the generic placeholder name datawith names of the students in the course. A third worksheet contains a list of groups, the first andsecond experiment each group is assigned to perform, and the lab session number to which thatgroup is assigned.If the number of groups is changed, the data in columns A through G for those groups must bepopulated on the Group Data sheet. If the number of experiments or lab days is changed, the data 300 Number of Deviations from Target Value
also conducted with respect to the “Feedback Controls” comic, which depicted theindividual PID tuning parameters proportional gain (KC), integral time (τI), and derivative time (τD) asboxers, with the strength and speed of their punches relating to the impact that the respective tuningparameters would have. An instructor who had taught a section of Process Controls in both the fall andspring of the 2014-2015 academic year, implemented the comic in a section of both semesters in the2015-2016 academic year. A similar exam question was given to students in all four semesters thatdirectly addressed the effects of the individual PID tuning parameters. Class sizes varied, as reflective of the growth in the enrolled students at Northeastern (10