instance, it is assumed that students learn debugging by havingexperience with debugging [13]. However, a study by Whalley and colleagues revealed thatstudents’ reflections on their experiences with debugging tend to be negative [14]. In this study,students expressed that exploring strategies such as print statements frequently will make themmiss the program’s general idea, forcing them not to follow a methodological approach [14].Although debugging is a challenging task, it is also an essential skill that students must master toacquire other computational thinking skills [15]. Consequently, exploration of students’debugging skills is essential to develop teaching and learning strategies that fully explode theiralready-in-place preferences and
Science Outstanding Mentor Award. ©American Society for Engineering Education, 2023 Labor Based Grading in Computer Science - A Student Centered PracticeAbstractInnovation in teaching in STEM fields was explored widely during the COVID pandemic in 2020. Thispaper describes the adaptation of labor based grading for computer science courses. Labor based gradinghas been developed for language and writing courses by shifting the grading focus from summative examsto formative and reflective assessments. The method was tested in several computer science courses withtwo different instructors during the 2020-2021 academic year. Students were surveyed to understand howthey perceived grading methods
projects. Thisresearch also analyzes how adult learners interactively learn, reflect, and apply their AIknowledge to examples drawn from their workplace, while improving their understanding andreadiness to implement AI technologies effectively.Our three-day workshop centered around enriching and engaging learning about AI technologies,ethics, and leadership, featuring topics like supervised learning and bias, AI strategy, andgenerative AI. Apart from discussions, the workshops incorporated hands-on learning with digitaltools, robots, problem-solving scenarios, and a capstone project. Participants were 44 leadersfrom a large government organization. Their learning was measured through pre- andpost-questionnaires on AI leadership, knowledge checks
it well worth the effort. The opennessof project topics has led to student creativity and expression in class projects, including theembracing of their unique identities and exploration of more advanced materials under instructorguidance. Projects that address a gender-specific, interest-specific, or queer concern also letstudents (the project makers and their classmates alike) understand that computing applies inmany disparate domains and there is great value to a diversity of voices in technology. Thispaper describes the approach, general project design outline, the ethical reflection embedded inthe project, and experiences from several years of teaching (since Fall 2017). A list of studentprojects with brief descriptions is included so
insight into the effectiveness of theassignment and which parts are most difficult for students to understand. Students alsoresponded to the reflection prompt “What was the most surprising or interesting part of thisactivity.” The responses were analyzed for common themes, which were the usefulness ofvisualizing memory in understanding the concepts of stack frames and buffer overflow, theprevalence of buffer overflow vulnerabilities in publicly available code, and how easy it is toexploit a buffer overflow vulnerability. Thus, this assignment shows promise in helping studentsto understand a difficult concept, and in emphasizing the importance of avoiding buffer overflowvulnerabilities.IntroductionSoftware vulnerabilities in commercial products
]). The SerenePulse webapp harnesses awebcam or selfie camera to capture heartbeats by analyzing fluctuations in light intensity reflected from the skin,a fundamental principle of rPPG technology.HRV metrics In this research, we build upon previous research [16] that detailed on HRV metrics and stress analysis. Heartrate variability (HRV), calculated from the input of rPPG, inter-beat intervals is a crucial physiological markerthat offers insights into the autonomic nervous system’s (ANS) functioning [16]. It reflects the dynamic interplaybetween the sympathetic and parasympathetic branches of the ANS, highlighting the body’s adaptability to stressand relaxation states [39]. Among HRV metrics, SDNN is indicative of autonomic flexibility and
computing is the reality of the computing education “culture” in the U.S.being primarily one-note (e.g., white-men)—including faculty, students, and professionals—which instigates perpetual curricular and non-curricular hurdles for members of non-majoritygroups to overcome. To attain their fit within computing, students must navigate the computerscience culture by adopting norms and values that are reflective of the majority-group [22]. Notbeing able to adopt these norms and values impacts students’ fit within computing contexts and,ultimately, their retention.Culture is a compelling explanation for underrepresentation in computer science. This identifiedone-note cultural concern in computing contexts where non-majority computing students
’ understandingof the overall module to see whether they meet the module objectives and a survey withopen-ended questions to help students reflect on their learning and experiences with the module,the second of which we discuss in more detail in the next section. Below are example quizquestions, with the correct answer choice italicized, relating to each of our three learningobjectives. • Question related to Objective 1: One student gives work to another, knowing that the student is going to copy the work directly and submit it for credit. Who has committed an academic violation? Answer choices (choose one): (1) Both the student that copied and the student that provided the material. (2) The student that provided the material. (3
simulation is running in Tinkercad Circuits. However, the output in the serialmonitor will reflect whichever Arduino was selected at the beginning of the simulation start. Forexample, while interacting with the potentiometer, only the analog circuit (lower one in Fig. 2)will display output in the serial monitor. In contrast, if the student clicks on the upper arduinobefore clicking the StartSimulation button, s/he will notice the serial monitor starts displaying0 (the default digital output when push button is not pressed) on the serial monitor. As soon ass/he presses the push button, the serial monitor will print 1 and then go back to the default 0state.Graph Output: Tinkercad allows to visualize the circuit output data in graph format. Though
]. With the increase in research publications, the focus on impact indicators has broadened,with citation counts remaining a widely accepted measure. Yet, they are not direct measures ofquality [7]. Despite controversies around these metrics, they continue to be used in academicdecision making. An additional metric that is being used more for evaluating scholarship are downloadcounts [8, 9]. Using downloads reflects a broader view of research impact, considering the actualusage and dissemination of scholarly works. While there is a correlation between downloadmetrics and citations [10], there are situations where this is not the case. For example, papers withfewer citations might be extensively downloaded and used by practitioners
explained to students as a note-taking tool to distill their understanding of Python. For students theyare meant to act as personal documentation of Python’s syntax and semantics. In this research, rulesnotebooks were a window into students’ conceptions of Python’s syntax and semantics. We view therules notebooks as reflective activity germane to the conclusion and discussion phases of IBL.5 Data and Preliminary AnalysisOur analysis of the data from this course is ongoing, and we are collecting more data on a second iterationof the course. This work-in-progress paper reports on preliminary review of rules notebooks as well aswritten assignments and observations from the course. Preliminary analysis of students’ rules notebooksindicated that
. DiscussionThis research aims to examine students’ in situ demonstration of the cognitive and behavioralskills associated with algorithmic thinking in an introductory computing course in engineering.Our findings indicate that while students are frequently able to produce working code that solvesa wide array of computing problems, their submissions do not always reflect the cognitive skills,such as algorithmic thinking, that are central learning goals in introductory CS education. Thesefindings lead us to question the utility and appropriateness of autograders for assessing andevaluating student learning, particularly as it relates to complex cognitive skills in CS education.Existing research suggests instructor feedback supports students’ learning beyond
from participating in the surveys and interviews in the study.Section 2 (Evening): 13 students were included, constituting 24.5% of the sample. Theseparticipants were 25 to 36 years old, and three declined to participate in the surveys andinterviews.Section 3 (Evening—Control): Ten students formed this section, representing 18.9% of the totalsample. All participants in this section, aged between 25 and 36, completed the surveys andparticipated in the interviews.The gender distribution among the participants was 11.32% female students and 88.68% malestudents, reflecting the typical demographics of industrial engineering programs in the region.This study set out to explore students' perceptions of the effectiveness of active learningcompared to
Reflections, Review Review Review Review 4:15 - 4:30 Feedback, 4:30 - 4:45 Photos Reflection Reflection Reflection Reflection Closing and Thank You! 4:45 - 5:00emotional intelligence [30, 31], and effective communication skills [32].Introductory technical skills were covered early in the Guild workshop so that the participantscould start applying these skills and programming languages
- Cybersecurity Planning and Management (CPM)CPM-1: Examine the placement of security functions in a system and describe the strengths andweaknessesSource: Final Project Individual Reflection Question 2 which provided a network diagram andasked students to identify strengths and weaknesses. EAMU Vector (19,0,0,0)CPM-2: Develop contingency plans for various size organizations to include: businesscontinuity, disaster recovery and incident response.Source: Final Project Individual Reflection Question 3 which provided three scenarios and hadstudents answer how to achieve various goals. EAMU Vector (18,1,0,0)CPM-3: Develop system specific plans for (a) The protection of intellectual property, (b) Theimplementation of access controls, and (c) Patch and change
people and circumstances that differ from those with which students are familiar. Frequent, timely, and constructive feedback. Periodic, structured opportunities to reflect and integrate learning. Opportunities to discover the relevance of learning through real-world applications. Public demonstration of competence.While not all HIPs address each element to the same degree, the list provides a standard forjudging the quality of implementation. It could potentially be used to assess the quality of otherevidence-based curricular and co-curricular activities as well.The most common outcome studied across all high-impact practices is student retention andacademic performance (grade point average). For both measures the result is
observed but no long-term career outcomeevaluation. These studies collectively demonstrate the positive impact of inquiry-based learningin scientific education, albeit with a need for more extensive, long-term evaluations.Dickerson et al. [20] employed a distinctive approach to foster reflection among engineeringstudents within the context of a digital circuits course. This method integrated computer-basedsimulation for digital circuit design with reflective thought prompts administered after a midtermexam for post-exam analysis and contemplation. The study also underscored the significance ofemploying thought-provoking question prompts designed to voluntarily elicit comprehensivereflections after a significant milestone event, such as a midterm
are organized into “guided problem sets”,each containing a series of exercises related to a single problem or skill. Guided problem sets arenot intended to replace written homeworks or exams, but rather to replicate the kind of interactiveleading questions that a student might be asked in a discussion/lab section or in office hours.The design goals for these guided problem sets reflect the goals for other components of the course,including lectures, labs, and grading rubrics. First, for each type of problem, auto-graded exercisesshould reinforce the solution process recommended in other parts of the course for that problemtype. Said differently, we want to proved the students with working examples, not just more workedexamples. A good example
data manipulation at a designatedmemory location.Figure 4: Visual depiction of data placement in the memory in the Data Segment of RARS after programexecution.3.2 Developing a Paint ApplicationIn the lab, students develop a simple "Paint" application on an emulated RISC-V system, akin to initialgraphical projects in HLL courses. This application uses keyboard inputs to create Bitmap displaypatterns, with color addresses representing pixels. The task involves setting a starting pixel and usingkeyboard commands for drawing, reflecting basic HLL logic operations and control flows. This lab'sstructure is in line with notional machine principles as described in [9], sharing pedagogical purposeswith lab 3.1. With regards to the Focus aspect, the
information presented was not helpful for the scholars in theprogram because the presenters did not discuss the funding opportunities, which is essential forlower-income students, as we found in our qualitative study [4]. Hence, we asked the PIs tochange messaging around the grad school within computing, which was reflected in the recentyear showcase, and we find that the students’ understanding of graduate school functions hasimproved. Similarly, we are trying to bridge the gap between students’ perceptions of thesepathways and the institutional messaging around them. Being a stakeholder, the educationresearch team within Flit-GAP also plays an essential role in the computing education ecosystemto meet the students where they are.4 Methods: Data
relationship of certain factors to students’ sense ofbelonging. Results from the analysis of data from 380 student participants indicated that“students’ sense of belonging and retention are crucially influenced by both academicengagement and social engagement, but independently” [13]. A 2023 follow-up study furtherrevealed that their surroundings and personal space also affected students’ sense of belonging.“Surroundings equate to participants’ living space, and geographical and cultural location, whilepersonal spaces refer to life satisfaction, life attitudes, identity, and personal interests” [14]. Ahnand Davis (2023) further recommend that all four domains (academic and social engagement,surroundings, and personal space) be considered and reflected
Bit (LSB) of the opcode governs theselection between two results within the same category (logic or arithmetic). In Fig. 2, theopcode is set to “11,” indicating the operation Y = A – B. Initially, the input B undergoes theconversion to its 2’s complement format, followed by addition to A, and the result is showcasedin the hex-display on the right. Modifying the opcode will accordingly reflect the correspondingresults. Opcode Operation 00 AND 01 OR
spy gadgets and their countermeasures, consumers are drawn tospy detector devices. [6]. Spy detectors typically have a common set of features, including RFdetection for wireless cameras and microphones, magnetic field detection for GPS trackers, andflashing LED infrared lights that capture camera lens reflections [1][2]. The more expensivedevices come with sounds and haptic vibrations to alert for possible detection. Unscrupuloussellers make inaccurate claims that devices prevent camera spying when, in reality, the devicesonly provide detection, giving their customers the false impression that a camera is no longercapable of spying on them.This paper presents a project by a senior capstone team of four students who aimed to develop anadvanced
F. Instructor Resources The blueprint provides reflective checkpoint questions for These outcomes have associated questions/problems that instructors to facilitate communication with students. Instruc-students must be given and assessed on throughout the tors get a list of questions to interact with students such assemester. “What is working well or not working to help you learn?”and “Is the pace of this course too slow, just right, or too C. Faculty Satisfaction With Blueprintfast?” We will also survey the first
training project realization would be part of the moreall-encompassing scope of ITL as discussed in the section “ITL future work and applicability toscalability” . As with any cultural change to how students understand learning, it is advisable that instructorswho are adopting Inquiry over Transmission spend time explaining the method to students, sharing thevisual diagram of the different stages of Inquiry, and providing scaffolds, such as graphic organizers thatprompt students to reflect while engaging in what may be a very new and foreign approach to learning.The more explicit instructors can be about the value they place on learning through Inquiry, how thishappens, challenges students face initially, and other factors, the better
limit how much educators can help students prepare, it may be worthproviding training to faculty. Whether through industry partnerships to offer workshops or todirectly administer mock interviews, providing such experiences for educators could ultimatelyhelp to foster empathy for what the hiring process may entail and could raise awareness of theexpectations for those who may be unfamiliar with it. Education can be valuable and canempower and equip faculty to better aid their students as well.7 Limitations and Future DirectionsThe study conducted a focus group of a subset of individuals across the United States. However,the experiences and voices represented may not be reflective of all institution types or of alleducators
@iupui.edu raj.s@austin.utexas.eduAbstractIn this full research paper, we aim to enhance the instructional delivery of the CIT 21400(Introduction to Data Management) course at IUPUI to improve students’ learning experience andto engage students better as they learn and apply the foundational database concepts. Introductoryprogramming courses such as database programming and design represent crucial milestones inIT education, as they reflect students' ability to solve problems and design appropriate solutions.But, for novice programmers learning SQL (Structured Query Language) programming andlogical database design concepts is a challenging task because while writing SQL programs,students not only have to apply
of programmatic efforts for the first cohort year. We recognize that thestudents in the program, in some ways, reflect the views typical engineering and/or computingstudents, as many programs emphasize internship pathways as crucial. In other ways, thestudents in the program have higher demonstrated financial needs than other students, which mayincrease their economic anxiety and desire for a secure well-paying job.We are conducting qualitative interviews and observations on the program as well, discussed inanother paper [15]. As we continue to provide feedback to improve the responsiveness andmessaging of the programming, we will continue to monitor the overall patterns of interest in thepathways and, eventually, the pathways that students
cybersecurity research, counseling students, assisting with open days for new students, contributing to curriculum enhancements, and proposing a new club to support women in the industry, SWCSI (Supporting Women in the Computer Security Industry). He excels at guiding students in subject choices based on interest, ability and skills. His continual quest for knowledge and broadening his skills has proven beneficial to his students and his professional evaluations reflect this in perfect teaching scores. Additional awards, societies and honor groups include: 2018 Expert Level Instructor Excellence Award – Cisco Networking Academy. 2017 Instructor 5 Years of Service Award – Cisco Networking Academy. 2017 Excellence in CCNA
. 1849454.and tidal energy are becoming increasingly significant. Numerous breakthroughs are being madeto transform these renewable energy sources into forms that may be used. The Current-Voltage(I-V) and Power-Voltage (P-V) curves from the solar array simulator will be generated andplotted during the simulation of solar cells in the MATLAB environment.Silicon Nanowires- Fabrication and Optical Characterization (Norfolk State University)The creation of effective solar cells and intelligent lighting is the aim of this research. Usingmetal-aided chemical etching (MACE), silicon nanowires (SiNWs) will be created, and theireffectiveness in lowering the surface reflectance of silicon wafers will be examined. Optical andscanning electron microscopy