influencedtheir grade, (3) impressions of other members in the study group, (4) opinions about the mostvaluable and least helpful parts of the study group and (5) reflections on how participating in thestudy group changed their confidence in completing the engineering degree and their feelingsabout being a student at ASU. Pseudonyms were given to participants to ensure theconfidentiality of the interview.ResultsThere were 22/50 respondents for the post-survey (response rate of 44%). Of these, 16 could bematched to the pre-survey, due to the fact that some students did not use the same personal codethat they generated on the pre-survey. Of the 16, 14 had been placed in PLSGs, and one hadbeen placed in TARs (one student did not identify a group).Table 2
)they foster collaboration; (e) they involve meaningful reflection; and (f) they allow competingsolutions and diversity of outcomes. Importantly, the tasks are similar to the type of workstudents will experience as professional engineers (e.g., hydrologic modeling, analyzing trends indata, and justifying decisions) and the product of the module is polished and realistic (e.g., anassessment report, a model, or code).Previous research shows that student learning is greater in courses where tasks regularly promotehigh-level reasoning and problem-solving and lesser in courses where the tasks are scripted orprocedural [25] - [27]. Litzinger et al. [28] researched the learning processes that support thedevelopment of expertise. Their findings
engineering major's significancein other countries.Theoretical-based coursework is one of the contributing factors of large numbers of first-year E/CSleaving the engineering field [10]. Such coursework makes relating concepts taught in class toreal-world scenarios quite difficult and creates a negative feeling of engineering concepts amongE/CS students. Students tend to enjoy their coursework if they can see the benefits in real-worldapplications and the flexibility to solve real-world problems. E/CS curriculum should be updatedaccordingly to reflect technological advancement in the field. Teaching students, especially first-year students, outdated technologies and innovation could discourage students from continuing intheir majors. Students might
into being when people select and activate it by taking appropriate action) and created(i.e., the environment in which people create the nature of their situations to serve their purposes)[22]. While research has yet to examine the impact of these types of educational environments canhave on student learning, empirical studies have corroborated that students tend to adjust theirlearning strategies on the basis of their perceptions of their learning environments [11, 31]. Placing these elements together, Figure 1 illustrates the general conceptual framework for thisstudy. Engineering students enter an online learning environment with their self-directed learningcapabilities, which are mainly reflected in their motivation for learning and
clear, long term goals to complete tasks.11. I had confidence in each team member to contribute his/her fair share of what was required.12. This team helped me understand the material presented in this course.13. Deleted – incomplete question-14. Our team did not function well as a team; we did not establish any process to hold one another accountable nor did I ever know what individuals were responsible for. (Reverse)15. Working on this team made me realize that some things about myself (e.g., communication ability, leadership) that I was not aware of.16. My team reflected upon its goals in order to plan for future work.17. My team used a process/method (e.g., code of cooperation) to hold each member accountable.18. This team
-quality interactions and higher scores in this study could have beeninfluenced or caused by other variables beyond our control; more controlled studies are neededto validate these findings.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No. 1628976. Anyopinions, findings, conclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation.References[1] D.H. Jonassen, and W. Hung, “All problems are not equal: implications for problem-based learning,” Interdisciplinary Journal of Problem-Based Learning, vol. 2, no. 2, pp. 6-28, 2008.[2] D.H. Jonassen, “Instructional Design Models for Well
reflect the self-regulative learning experiences oflearners.The MSLQ in the Freeform context In 2008, an active, blended, and collaborative (ABC) teaching and learning environmentfor a core engineering science course (Dynamics), named Freeform, was developed and adoptedby a team of mechanics instructors [28]. With the goal of a student-centered classroom, Freeformtransformed a lecture-based pedagogical environment to a highly-networked pedagogicalenvironment. The hybrid nature of course resources (i.e., instructor-produced videos, hybridtextbooks which combined a traditional textbook and significant white space for note taking, anda course blog) allowed the students to actively, collaboratively engage in the class and managemultiple
will use the list of themes and codes developed by Garcia etal.’s (2019) servingness framework as a starting point of a priori codes, while also employingopen coding to identify structural characteristics that are specific to this context and do not fit thelist of codes in Garcia’s study. To identify the cultural characteristics, we will utilize valuecoding, defined by Saldaña (2016) as the application of codes unto data that reflects the values,attitudes, and beliefs about the phenomenon under study [21]. In this case, these codes will applyto the institution’s values, attitudes and beliefs about their role in serving Latinx students. Oncethe structural and cultural characteristics have been identified, we will conduct a second round ofcoding
Exposition, Chicago, IL, 2006. 5. Friess W.A., and Davis M.P. “Formative Homework Assessment Strategies to Promote Student Self-Reflection and Improve Time Management: APilot Study”. \ Proceedings of the ASEE NE 2016 Conference, Rhode Island, RI, 2016. 6. Lura D, O'Neill R and Badir A. “Homework Method in Engineering Mechanics”. American Society for Engineering Education Annual Conference & Exposition, Seattle, WA, June 14 – 17, 2015. 7. O'Neill R, Badir A, Nguyen, L, and Lura D. “Homework Method in Engineering Mechanics, Part 2”. American Society for Engineering Education Annual Conference & Exposition, New Orleans, LA, June 26 – 29, 2016. 8. Trautwein U., and Köller O. “The Relationship Between
before beginning and again after completion of the video term-paper project.Both control and intervention groups received 45 minutes of media literacy instruction afterviewing the first set of videos.The media literacy instrument was developed in a style similar to that of previous work of Hobbs& Frost 24 Arke & Primack, 25 and Ashley, Lyden, & Fasbinder.26 Using Hobbs’ 14 conceptualframework of media literacy of “access, analyze, create, reflect and act” as a guide, theinstrument’s questions were: 1.) Who is the sender of this message? 2.) Describe the main message of the video using your own interpretation. 3.) Are there other possible interpretations of this video’s main message? 4.) Who is the
used whenappropriate.In conclusion, whilst the first cycle of the Changing Futures Project has been immenselysuccessful, it is extremely resource intensive and would not have happened had the twoacademics responsible not had a personal desire to support students. No additional funding ortime was allocated to run the project which continues to be administered on a mixture of good-will and unpaid overtime! Despite this, the primary outcome of seeing the fortunes of some ofthe weakest students being turned around has been exceptionally rewarding. In reflecting uponthe project, ten key recommendations for institutions, colleagues and students are made:Recommendations for Institutions: 1. Financial Resources: Should be ring-fenced to provide a
GeneralizedObservation and Reflection Platform (GORP), hosted by UC Davis(https://cee.ucdavis.edu/GORP). While there are limitations to the GORP tool, the advantage ofbeing free, intuitive, and able to be run on a touch screen laptop far outweigh limitations. The dataare captured in real time and outputs as a spreadsheet file, which reads the categories as a functionof time points. The resulting data file can be manipulated in MATLAB or other programs. Table 2: Codebook and Numerical Values Assigned for Data Processing Numerical Level Definition of Level
thefinal evaluations that co-op and internship students and their employers are required to completeat the end of the work term. In total, 451 students completed the instrument, and 373employers—response rates of 92% and 76% respectively. Note that sample numbers reportedbelow may be lower given the students and employers who responded to particular items as “NotApplicable.”ResultsPrior to conducting the statistical analyses reported below, we reverse coded the negativelyphrased items so that higher scores reflected better communication skills for all items. Theseitems are noted with ** in Table 1 and Table 2 below.To answer Research Question 1, whether the instrument measured students' oral communicationskills reliably for both students and
defining, designing for, and planning for assessment ofstudent motivation is the QFD. This method has been effectively used to design learningactivities that motivate students and ultimately produce positive measureable results in academicsuccess. Learner centered games that focus on student interests provide an effective pathway tostudent motivation and academic success. Successful games include simple web based gamesthat may take only a few hours to create to complex gaming environments that form a frameworkfor an entire course. Students that are motivated through specifically designed course activitiescan not only provide opportunities to create environments that motivate and engage students tothink reflectively about engineering content and to
presentation and discussion of technical and computational issues projects should address 3. Follow-up Reflection Assignment 4. Review computational approaches in final reports Figure 2. Schematic of the instruction and assessment in BME design class.Details about each of the numbered steps are provided below.1) The invention activity is given as a homework assignment. Students are asked to review a previous team’s report with a critical eye regarding the technical/computational components of the team’s work. The homework includes two invention activities. In the first, students are asked to generate a list of the technical details that all design
bydegree requirements, availability of suitable textbooks, and other resource and pedagogicalissues. So the perception that faculty don’t immediately respond to good assessment data maysimply reflect the conservative nature of the academy in responding to curricular issues.In addition to the work on institutional change models, other authors have attempted to addressfactors that support or hinder institutional change. For example Litzer6 reports that affectedfaculty and administrators must clearly perceive value in the changes proposed.New Elements to the Change ModelWhat seems to be missing from these change models is the role time plays in institutionalization.Responding to faculty prudence regarding change, an important aspect of sustaining
Page 14.1295.10observational data that educational researchers routinely encounter and can be used in a varietyof settings to gain deeper insight into the factors affecting educational outcomes.AcknowledgementThis material is based upon work supported by the National Science Foundation under award0757020 (DUE). Any opinions, findings and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation (NSF).References1. National Science Board Science and Engineering Indicators 2002; NSB-02-1; National ScienceFoundation: Arlington, VA, April, 2002.2. Bernold, L. E.; Spurlin, J. E.; Anson, C. M., Understanding our students: A longitudinal
assigned to theIndividual Beliefs theme category tended to be more neutral. The number of responses sorted bytopic is generally even with an exception of the Teaching (Curriculum) topic, which had 324comments. For future work it could be useful to unpack this item into sub-groups for furtheranalysis.The School theme category topics are generally ordered with more negativity than the groupingof the Individual Belief theme category topics. It is interesting to note that both Co-op and Moneyare exceptions here. It may be that these two topics are much more concrete than the other moreabstract items or that, in reflection, the categorization of each should be reconsidered. In otherwords, finding benefit from experiencing a co-op experience and being
-351.9. Aleven, V., & Koedinger, K. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science, 26, 147-179.10. Chi, M. T. H., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improve understanding. Cognitive Science, 18(3), 439-477.11. Lin, X. D., & Lehmann, J. D. (1999). Supporting learning of variable control in a computer-based biology environment: Effects of prompting college students to reflect on their own thinking. Journal of Research in Science Teaching, 36, 837-858.12. VanLehn, K., Jones, R. M., & Chi, M. T. (1992). A model of self-explanation effect. Journal of the Learning
conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect theviews of the National Science Foundation. References1. National Academy of Engineering, Changing the Conversation: Messages for Improving Public Understanding of Engineering. 2008, Washington, D.C.: The National Academies Press.2. Pearson, G. and A.T. Young, eds. Technically Speaking: Why All Americans Need to Know More About Technology. 2002, National Academy of Engineering.3. International Technology Education Association, Standards for Technological Literacy: Content for the Study of Technology. 2000, Reston, VA: Author.4. National Center for
order to examine the relationship between outcomeexpectations and occupational preference in more depth, the detail provided by Vroom’sExpectancy Theory3, specifically the valence model, is useful.Social Cognitive Career Theory2 can be used as a lens through which to examine which types ofoutcome expectations women and men have about an engineering career. According toBandura’s social cognitive theory4, outcome expectations are the anticipated consequences of acourse of action and can be physical, social, or self-evaluative. For example, a student mightexpect that the outcome of earning an engineering degree will be making money (physical),becoming well-known (social), or developing new knowledge (self-reflective). Lent, Brown,and Hackett used
ofadditional funding. Over this time, a number of different approaches to leading the changeprocess have been applied. In reflecting on our experiences, it is apparent that we employeddifferent approaches to facilitate change depending on the circumstances, in a sense applyingsituational leadership, and also that our change model has evolved much along the linesdescribed by Clark et al.,2 shifting to a model that always has the question of how we willsustain an innovation built in from the outset.To write this paper, we have selected projects from which we drew significant lessons about theprocess of implementing and sustaining change. For each, we briefly summarize the approach
Page 11.381.9 Proceedings of the 2006 American Society for Engineering Education Annual Conference & Exposition Copyright © 2006, American Society for Engineering Education interdisciplinary team has a complexion that extends beyond selecting individuals to participate. 6. Our historic Program has its roots in a 30-year old vision not far removed from that more prominently stated in Engineer of 2020; self-reflection promoted by this project has reaffirmed our institutional commitment to the principles, values, and perspectives of our mission statement: ….to provide a select community of CSM students the enhanced opportunity to explore the interfaces
were chosen based on prior knowledge of their use of nontraditional teachingmethods as well as their self-selection into the study. The final study sample represents a mix ofgender, institution type, Carnegie type, and discipline, and the demographic and characteristicdata are reflected in Table 2. The total number of students used in the analysis was 997, andpairwise deletion was used to handle missing data across survey items.Table 2Survey Population and Characteristics of Engineering Instructors Course Instructor Institution Carnegie Course Number of label gender type classification* discipline** students 1 F
, is a social and discursive practice and understanding itrequires paying close attention at the micro-level. The concept of genre, in turn, highlightsthe recurrent and situated nature of discursive practices, and provides robust methodologicaltools for studying the production, reproduction, and change of discourse. For example, instudying the electronic discourse of a group of computer scientists, Orlikowski and Yates[18] identified the repertoire of genres enacted by the participants over time and showed howthese discursive actions reflected their collective purposes as well as the shared norms andrelations of their occupational community. Similarly, learning in any given setting that relieson repeated discursive acts, which can be
following conclusions are warranted: • Student’s performance at the beginning of semester is highly correlated to their performance throughout the semester. This enables developing an early alert system by monitoring students at the beginning of semester. • Early semester homework assignments, mid-term exams, and in-class practice problems can be employed as Students Performance Indicators (SPI) for developing the prediction model. • Among the considered SPIs, the in-class practice problem indicator that reflects the active involvement of students in class exercises showed the highest regression coefficient. This emphasizes the importance of student’s participation in class activities on their
studied using the implementation in a variety ofengineering schools.Acknowledgements: Support for this work is provided by the National Science Foundation Award No. DUE 1504692 and1504696. Any opinions, findings, and conclusions or recommendations expressed in this paper are thoseof the authors and do not necessarily reflect the views of the National Science Foundation.References:[1] Crawley, E.F., Malmqvist, J., Östlund, S., Brodeur, D.R., and Edström, K., "Historical accounts of engineering education", Rethinking engineering education: Springer, 2014, pp. 231-255.[2] Froyd, J.E., Wankat, P.C., and Smith, K.A.," Five major shifts in 100 years of engineering education", Proceedings of the IEEE Vol. 100, No. Special
International Conference on Web and Open Access to Learning (ICWOAL), 2014.[3] E. D. Lindsay and J. R. Morgan, “Passing our students while we fail upwards: Reflections on the inaugural year of CSU Engineering,” in 45th Annual SEFI Conference, Terceira, Portugal, 2017.[4] J. R. Morgan, E. D. Lindsay and K. Sevilla, “A "MetroGnome" as a tool for supporting self- directed learning,” in 2017 Australasian Association for Engineering Education Conference, Sydney, Australia, 2017.[5] M. van den Bogaard, C. Howlin, E. Lindsay and J. Morgan, “Patterns Of Student's Curriculum Engagement In An On-demand Online Curriculum,” in 46th SEFI Conference, Copenhagen, 2018.
EffortStudent effort is known to be a significant predictor of performance on low-stakes tests [22].During ESO testing, proctors observed that some students testing in-class clicked throughquestions toward the end of the test, reflecting decreasing effort. Results from the ESO showed acorrelation between time spent on the core test components and final core score, suggesting thatstudent effort did impact achievement.However, previous work on PIAAC engagement suggests that the proportion of disengagedrespondents from Canada with educational attainment greater than high school is less than 5%[30]. Only 4.2% of the students in this sample were filtered out because of low time spent ontest, which aligns with this previous evaluation of disengaged
in implementing these steps also vary, though all havecommon traits that quality instruments share [4], [5], [1], [6], [7]. The procedure outlined byNetemeyer [2] was the basis for several other established instruments, and served as a drivinginfluence for this project.Netemeyer suggests a linear model of instrument development motivated with empiricalevidence. The critical first step, is to clearly define the traits or abilities being measured.Accurate definitions are necessary as they will inform item creation and the overall character ofthe instrument. The definitions should be informed by theory, and accurately reflect the contentdomain being measured. Literature and other appropriate sources should be thoroughly reviewedto best inform