data for a planned multiple semester longer term project.This paper contains (1) motivation and goals for this work, (2) outcomes and learning objectives,(3) instructions on how to design this kind of assignment, (4) the video assignment write up, (5)the rubric for the video, (6) the rubric for peer feedback, and (7) the rubric for reflection. Thispaper focuses on the structure and instruments used during the course.About the CourseArtificial Intelligence (AI) is being used to tackle more and more of the real-world problemsaround us. EECS 4901 Special Topics: Introduction to Artificial Intelligence will introducestudents to the fundamentals of Artificial Intelligence (AI). During this course students will lookat various problems being solved
University of California, San Diego sserslev@ucsd.edu Madison Edwards Chemistry and Biochemistry University of California, San Diego m4edward@ucsd.edu Abstract This study explores how industry internships, paired with scaffolded reflection, shape student attitudes and learning behaviors. Building upon the literature on student motivation, we seek to answer the following question: how do internships influence student attitudes towards their studies and their future approaches towards learning? Data at three critical points in a student
homework, with quickfeedback. A final hurdle was that this was the author’s first time teaching Vibrations. Therefore,it was necessary to prioritize lesson plan preparation over delivery logistics. This precluded timeintensive efforts such as learning complicated software or prerecording lectures in an instructionallab environment.Mastery learning (or learner-centric) techniques introduced by Bloom in the 1970s and expandedby researchers over the last half century have an established track record for enhancing studentlearning.1–3 In particular, periodic formative assignments are necessary and should be designed sothat students reflect on mistakes and adjust their learning efforts as needed. Within the Vibrationscourse, the mechanisms for formative
Paper ID #30213Curri: A Curriculum Visualization System that Unifies CurricularDependencies with Temporal Student DataDr. Stephen Michael MacNeil, University of California San Diego Stephen’s research focuses on how people collaboratively make sense of complex, ’wicked’ problems. Wicked problems are dynamic and constantly changing. They involve multiple stakeholders, often with conflicting requirements. To address these challenges, Stephen develops sociotechnical systems that col- lect, organize, and use data to support reflection and collective action. He received his Ph.D. at UNC in Charlotte and is currently a
NTP analogy, the telnet protocol offers a network administrator aquick way to set up a text-based console connection between a computer and a network deviceuses port 23. It can be shown visually as an individual (I) being able to establish a quick andconvenient connection with a network hardware device. The Network News Transfer Protocol(NNTP) uses port 119. It would seem like a problematic port number to memorize; however, ifone imagines looking at this number reflected in the mirror, it would be “911” -- which forreasons yet unclear to the author -- is what most news these days is. An open newspaper showsthe 119 port number with images and text regarding the news of the day. Email is an extensiveglobe-spanning system which can be shown by a
. Nextwe incorporate sklearn 40 so students can execute and explore the results of machine learningalgorithms. To prepare for machine learning content students watch bots videos 14 and they arealso assigned some ethics reflection prompts in response to Cathy O’Neil’s TED Talk 35 .The common thread across topics is the problem-solving heuristics shown in Figure 1. Weintroduce these early on and revisit them with each topic and explicitly point out when we areusing a strategy, or trying several of them, to solve a problem. For example we point out the useof concrete examples for solving encoding problems, developing algorithms, and initially usinghard-coded values in incremental web development. Another example is how students areexposed to
in both parts of the project.3.5 DeliverablesThe teams were required to produce mini-reports at the end of each part, in addition to an overallfinal report and presentation at the conclusion of the project. At the end of Part 1, teams had tosubmit a word document providing the answers to each of the clues, along with specificstrategies and steps they took to reach the answers. The teams also had to submit a worddocument at the conclusion of Part 2, including selfies in front of the target building and uniqueclue, alongside written descriptions of their physical observations and details about the uniqueclue. Final reports and presentations included consolidated versions of the mini-reports above, aswell as reflections about team challenges
institution, which may affect how well thesefindings can be generalized [12].When exploring which factors from high school are most predictive of college graduation,between standardized test scores (SAT and ACT) and students’ high school GPA, GPA isconsistently considered the winner, in terms of which variable has the greatest impact [13–15].The hypothesized rationale for this observation is that although standardized tests considerintellectual abilities in certain domains, the overall GPA considers different intrapersonal qualitiesas well that were useful for positive outcomes in college [15]. More specifically, although gradescertainly do reflect skill levels on specific content, it may also include individual factors such asstudents’ attitudes
one. They design and build it as aprototype. Then they test and revise it to meet the needs of their client successfully. Finally,student groups present their solutions and ideas in the whole class, and they are given time forself-reflection and final revision of their models.3. Implementation of Security Modules with Model-Eliciting Activities3.1 Incorporation of Cyber Security ModulesFor each of the 9 lessons introduced in the CS 1 course, an explanation is provided of how thatlesson was incorporated into the course curriculum. Table 1 presents the lessons and the MEAproject in relation to the chapter of the textbook that is covered at the time that lesson is introduced.The book used for the course was Starting Out With Java: From Control
addition, the data for number of minutesbetween the first and the last attempt did not reflect a consistent trend of one group taking moretime than the other. It is possible that these results are not the best metric of learning efficiency, Category Solution Explanation Expected This solution represents what we ex- numODD = 0; pected as a solution - a while loop that %Add your while loop here iterates through a range of numbers, n = 1 while n <= 7 checking if the current number is odd if rem(n,2) ˜=0 (and
specific system. Cache simulation tools provide support for diverse configurations ofthe system and help to capture the real world scenarios to ensure that the system performs at anoptimal level.We surveyed cache simulation studies to better understand the needs for cache simulation. Then,we designed numerous scenarios using different cache configuration and sizes to reflect thescalability. Keeping the focus on achieving maximum performance, cache associativity is alsoobserved and extensively studied to verify the gains in performance were made possible. Varioustypes of cache associativity were examined and their benefits and limitations are summarized. Wealso studies that the relationship between cache associativity and cache coherency. One
. This exposed our students tocollaborators among different fields, with their own terminology, goals, work methods andpractical approaches. Our paper reports on the initial experiment during the Fall 2019 term,involving two sections of an Artificial Intelligence class and one section of a Deep Learningclass. We are planning to continue this collaboration in the future.Keywords: Collaborative Learning, Interdisciplinary, Inter-Class teamwork 1. IntroductionStudents at California Polytechnic State University, San Luis Obispo (Cal Poly) are exposed topractical, hands-on educational activities throughout their course of studies, reflected by theuniversity’s “Learn by Doing” motto. In the Computer Science, Software Engineering andComputer
opinions, findings, and recommendations expressed in thispaper are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References 1. Utah Code and Board of Regent’s Policy Statements Regarding UVU’s Mission and Role: Planning, Budget, and Human Resources, UVU Planning, Budget, and Human Resources, September 21, 2018. 2. Information and statistics provided by the UVU Office of Institutional Research and Information – IRI. 3. U.S. Census Bureau, 2011, http://www.census.gov/popest/data/historical/2010s/vintage_2011/ , accessed on 3-14-2016. 4. Utah Department of Workforce Services, “College to career: Projected job openings in occupations that typically require a
or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of NSF.References[1] L. Farrell, “Science DMZ: The fast path for science data,” Sci. Node, May 2016. [Online]. Available: https://sciencenode.org/feature/sciencedmz-a-data-highway-system.php[2] E. Dart, L. Rotman, B. Tierney, M. Hester, J. Zurawski, “The science dmz: a network design pattern for data-intensive science,” in Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, Nov. 2013.[3] “NSF 2017 PI Workshop CI Engineer Breakout Survey.” [Online]. Available: http://www.thequilt.net/wp-content/uploads/NSF-2017-PI-Workshop-CI-Engineer- Survey_v4.pdf[4
subsequent sections detail the technology and design choices for this platform.4. Target MetricsTraditional IT organizations are currently siloed around aspects of service delivery: network and transport,data center, applications, security, etc [8]. This segmentation was driven by increasingly complextechnologies in each of these service delivery domains. While in smaller organizations these siloed arereflected in domains of expertise mastered by members of the staff, in medium and large organizations,5IT organizational charts identify specific teams for each of the domains mentioned. This segmentation isnaturally reflected in the skills developed by respective teams, the operating processes they develop, andthe tools used to manage the scope of the