The rapid expansion of artificial intelligence (AI) tools, including generative AI, is reshaping task completion and interaction, leading educational researchers to examine learning opportunities as well as emerging concerns in the present technological landscape. Despite ongoing discussions, it is less clear how students may envision such tools being integrated into computing education. We applied the Technology Acceptance Model and conducted a survey across three tertiary academic institutions in the United States, gathering quantitative and qualitative insights on n = 340 computing students' perspectives. Closed-ended items were examined with descriptive statistics, and an open-ended prompt around AI tool use in computing education was explored through reflexive thematic analysis. We found that 64.1% of students somewhat or strongly agreed that using AI tools (e.g., ChatGPT or GitHub Copilot) made them feel as though they were not truly doing the work themselves. Additionally, 48.8% of students somewhat or strongly agreed that they felt conflicted about using AI tools because competent computing/tech students should be able to figure things out without help. The qualitative themes spoke to instances where students may find adoption beneficial, like ''Expediting and enhancing learning, task completion, and organization,'' or problematic, such as ''Moral concerns and regard for social and environmental impact.'' Based on our results, we discuss strategies for teaching alongside AI tools and future considerations for computing educators and developers to support students' agency, ethical reasoning, and decision-making.

The disparity of women in computing and technology field is quite evident. There have been many national initiatives over the past decade that tried to enhance diversity in these fields. However, one group of population, returning women, have received little to no attention. Covid-19 pandemic has made this situation even worse by sharpening the inequality in America’s economy, where nearly eight times the number of women left the workforce compared to men last year. Yet, returning women, remain to be one of the largest untapped talent pools in the nation. The field of computing and Emerging Technology (EmTech) can use the untapped potential of returning women to fill the gap in workforce, which is growing at a rapid rate. Hence, to broaden participation and to understand the barriers and challenges faced by returning women to (re-)enter EmTech, a national virtual conference, RESET, was organized in 2021 amid the COVID-19 pandemic. In this paper, we present results from a mixed method study to investigate if the attendance at the RESET conference is a predictor of returning women’s elevated knowledge in (re-)entering EmTech education and/or workforce, and if the conference was successful in identifying resources that would facilitate transition of returning women in computing and tech discipline. In our quest to answer the questions we also report on – 1) challenges and barriers returning women face when pursuing computing degree, after a break, 2) challenges and barriers returning women face to transition to computing jobs, after a career break, 3) strategies and technical preparations that can be adopted to ease this transition, 4) level of satisfaction with the resources offered by the conference; 5) knowledge benefit from various technical sessions; 6) compliance with effectiveness of the resources offered; and 7) preparedness in pursuing EmTech education and workforce.

Recruitment, retention, and graduation of women in science, technology, engineering, and mathematics (STEM) training are critical needs in our nation [1, 2]. Within STEM, the computing and tech industry, specifically some niches, are expected to grow job opportunities more quickly than others. Emerging Technology (EmTech) concentrations like cybersecurity, data science, mobile development, machine learning, and cloud computing will have thousands of jobs in the next decade which will require a large pool of technical professionals. EmTech can use the largest untapped talent pool of women and returning women to fill the gap in the workforce. Hence, to understand the barriers and challenges faced by returning women to (re-) enter computing and tech fields, a three-day virtual conference, NSF RESET, was organized in March 2021. In this poster, we present the preliminary results on conference attendees' satisfaction level and effectiveness in facilitating resources to (re-)enter EmTech educational and professional pipeline.

Studies suggest women dropout of college and leave the workforce due to their family, finances, and military duty. However, women interested in (re-)entering the tech fields can be the largest untapped talent pool that may fulfill the needs of the future computing workforce. In this panel, five passionate women will share their experiences with identifying the challenges for women to re-enter emerging technology professions and the role of industry-academic relationship in facilitating such initiatives in order to develop future relevant initiatives.

introduction Re-Entering Computing through Emerging Technology: Current State and Special Issue Introduction Share on Authors: Farzana Rahman Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USAView Profile , Elodie Billionniere School of Engineering & Technology, Miami Dade College, Miami, FL, USA School of Engineering & Technology, Miami Dade College, Miami, FL, USAView Profile Authors Info & Claims ACM Transactions on Computing EducationVolume 21Issue 2June 2021 Article No.: 9pp 1–5https://doi.org/10.1145/3446840Online:23 April 2021Publication History 1citation76DownloadsMetricsTotal Citations1Total Downloads76Last 12 Months76Last 6 weeks12 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

One of the critical needs of the 21st-century workforce development is the recruitment, retention, and graduation of women in STEM fields. Research suggests that women drop out of academic programs and leave the workforce to deal with financial setbacks, tend to personal obligations and offer service in military programs. It is important these women, i.e. returning women, have pathways for reentry to college and opportunities to advance their careers. Some areas within STEM fields, such as Emerging Technology (EmTech) in computer science are expected to experience increases in job opportunities more quickly than traditional areas. The demands of these jobs can only be fulfilled by creating pathways for untapped STEM talent pools, including returning women. Therefore, we propose a panel to discuss the barriers and opportunities women face (re-)entering the STEM education and career paths, especially in EmTech fields. The panel of experts will provide different perspectives to spark conversation and reflection. The objective of the panel is to share experiences, advice, and ideas to advance the current state of knowledge about the complex challenges that women encounter and support structures for their reentry to the education and professional pipeline.

This paper compares social service selection techniques and analyzes the advantages and disadvantages of several approaches. We support our analysis with recent social service studies as well as exploring studies of commercial usage such as eBay, Amazon, etc. The three traditional areas of social service selection-reputation, recommender, and referral-will be the areas compared in detail. Service selection techniques often return a single value representing the rank of a service. Users of the service, however, may not always have identical needs and may be interested in ratings based on multiple categories. We feel this is an important aspect when comparing social service selection techniques. To address this, our investigation will also include examining the issues of adding quality of service (QoS) factors with social service selection.