Teacher dispositions have strong empirical and theoretical ties to teacher motivation, professional choices, and classroom practices. The attitudes and beliefs of teachers can mediate students' access to and experience with computer science (CS) instruction. This paper presents a baseline study to illuminate initial characteristics, beliefs, and experiences with CS of an elementary school teaching population in multiple districts across two states. As part of their onboarding to a large CS outreach project, U.S. teachers (N = 791) from partnering elementary schools (N = 28) completed the T-ABC, a survey instrument designed to measure teachers' beliefs about CS education, growth-mindset and self-efficacy. Prior CS professional development experiences were associated with statistically significant differences in the CS Beliefs and Self-Efficacy dimensions of the T-ABC. We present and discuss an additional principal component analysis producing a seven factor model, with psychometric overview of factor extraction and loading. Further we begin to define emergent factors such as teacher determination, teacher fear, and epistemologically confused positivity from this analysis. Identification and measurement of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences.

Instrument development is an important step towards unlocking the analytical power of teacher attitudes and beliefs towards Computer Science (CS). Teacher dispositions have strong empirical and theoretical ties to teacher motivation, professional choices, and classroom practices. To determine consensus desirable attitudes and beliefs, we analyzed 17 key documents produced by 12 national and international organizations associated with CS and the CS education reform movement. An analysis of 98 relevant coded segments yielded four dispositional targets: an equity orientation, a teacher growth mindset, and key beliefs regarding (career) outcomes and epistemology of CS. Statements crafted for these targets as well as self-efficacy were reviewed through an expert panel (N = 5) and a pilot study (N = 22) before the T-ABC was administered to elementary teachers in a large grant-funded outreach project (N = 772). Psychometric analysis demonstrates high reliability (Cronbach’s alpha = 0.89) and satisfactory extraction and loading onto a three factor model, with CS beliefs, growth mindset, and self-efficacy as major factors. Identification and measurements of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences.

We use "unplugged" activities to introduce parallel concepts in a first-year seminar for Computer Science majors. Student teams explore parallel approaches to computational tasks. Pre- and post-activity surveys, and a reflection paper, measure the impact of these activities on students' views about parallel programming. Our goal is to encourage parallel thinking about programming tasks before sequential approaches become ingrained. Computer Science curricula have traditionally focused on sequential approaches to programming, which were well matched to earlier computer systems. However, current systems almost all use multiprocessor CPUs, and are frequently used in clusters or networks of multiple computers. Recent curricular guidelines from organizations such as ACM and ABET recommend exposure to parallel computing concepts.

Three previous Working Groups (WG) have met at ITiCSE conferences to explore ways of incorporating cloud computing into courses and curricula by mapping industry job skills to knowledge areas (KAs) and KAs to student learning objectives (LOs) and using these as the framework for a repository of learning materials and course exemplars \citefoster2018, foster2019, adams2020. The ongoing value of the work of these WGs will be enhanced by validating the KAs and LOs and their mapping to current job skills and continuing to build a community of educators who will contribute to and benefit from the repository.

In the quest to study and deliver Computer Science (CS) education reform, attention to gate-keeping teacher characteristics is imperative. Broad research in teacher education has demonstrated that teacher dispositions are an important driver of teacher motivation, professional choices, and classroom practices. Identification and measurements of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences. We analyzed 17 key documents produced by 12 national CS organizations using a grounded theory methodology to identify desirable attitudes and beliefs associated with CS and the CS education reform movement. The documents included standards, corporate research reports, advocacy tools for CS education, and organizational documents of professional associations for CS and CS Education. The analysis yielded several important dispositional targets for description and measurement in the area of teacher attitudes and beliefs. An analysis of 98 coded segments related to dispositions yielded consensus attitudes and beliefs. Professional documents in CS highlight an equity orientation, a teacher growth mindset, and identify key beliefs regarding (career) outcomes and epistemology of CS. It is possible, based on this analysis, to create a profile of a teacher who demonstrates the attitudes and beliefs of a reform-aligned CS teacher, the CS "Champion''. Instrument development along these factors is an important next step towards unlocking the analytical power of teacher attitudes and beliefs.

We propose to strengthen the computer science (CS) curriculum by embedding parallel concepts in a required first-semester seminar taken by all incoming declared CS majors. We introduce students to parallel computing concepts through a series of unplugged activities so that students see parallel approaches as a natural form of solution to a task. We describe a pilot offering of the class and activities, with measurements and analysis of what students self-report and their performance on assessments.

Cloud Computing is a rapidly evolving field that is triggering a wave of innovations in various domains such as machine learning and artificial intelligence. Cloud skills are becoming essential for any technology-related profession. Furthermore, the accelerated adoption of cloud technologies by industry is increasing the demand for cloud-trained professionals. Thus, higher education institutions are offering training opportunities and programs in cloud computing, however, the lack of well-rounded and high-quality curricular materials continues to be a challenge for educators. A 2018 Working Group (WG) created a report that --among other artifacts-- described fourteen Knowledge Areas (KAs), with numerous Learning Objectives (LOs) for each KA, to teach cloud concepts. Expanding on that work, this WG will focus on providing a collection of resources that would eventually constitute a model cloud curriculum. By relying on two particular surveys: one that looks at the existing curricular offerings, and another one that maps knowledge areas to job titles in cloud computing, we plan to provide a dynamic and configurable curricular exemplars repository for the cloud community-at-large, following the popularity of hands-on, project-based learning methodologies as our primary focus.

As a prerequisite to ACM-IEEE CS1/CS2 curricula, common objectives of a CS0 course are: (i) to introduce CS to students who are interested, but do not have any prior CS skills, (ii) support student success while adapting to college life, and (iii) improve recruitment and retention of CS majors using the 'common first year' theme of many STEM programs. A previous CSO survey course at our institution focused on abstract logic, without any hands-on component, resulting in a CS0 "gate" course- a dull first encounter with computer science for most and an 'extremely fun and interesting' course for the few with pre-existing abstract thinking and reasoning skills. The missed opportunity to engage more students with CS, and thereby contribute to program viability and growth, spurred curriculum renewal. Given the existence of multiple high-quality offerings of CS curricula geared toward P-12 students, including at the AP-level, and also relying on our existing institutional partnership with a national non-profit organization dedicated to expanding access to CS in schools and addressing patterns of underrepresentation, we have implemented a new course based on a Computer Science Principles curriculum. This poster provides details of implementation as well as student experience and feedback with the first cohort of this brand-new course.

Cloud Computing has gained significant momentum in the last five years and is regarded as a paradigm shift away from traditional 'silo' based computing. It is no longer seen as a niche area of technology, offering a diverse range of scalable and redundant service deployment models, including Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), and Containers-as-a-Service (CaaS). These models are applied to areas such as IoT, Cyber-Physical Systems, Social Media, Data Science, Media Streaming, Ecommerce, and Health Informatics. The growth in cloud presents challenges for companies to source expertise that securely supports their business when migrating/deploying services to the Cloud - particularly Small-Medium-Enterprises (SME) with limited resources. The UK Government recently published the Digital Skills Crisis report, identifying skill-set challenges facing industry, with a shortage in cloud skills negatively impacting business. While cloud technologies have evolved at significant pace, the development of contemporary Computer Science curriculum in the further and higher education (HE) sector has lagged behind. The challenges faced in the sector includes the training of educators, institutional gaps (software and hardware policies), regulatory constraints, and access to cloud platforms. Collectively these challenges are significant, but not insurmountable. By embedding fundamental cloud skills throughout the educator and student journey, both stakeholders will be better positioned to understand and practically apply the use of appropriate cloud services, and produce graduates that can support the needs of industry. This working group (WG) aims to: i) assess current cloud computing curricula in CS and similar programs, ii) document industry needs for in-demand cloud skills, iii) identify issues and gaps around cloud curriculum uptake, and iv) develop solutions to meet the skill demands on core Cloud Computing topics, technical skills exercises, and modules for integration with contemporary Computer Science curricula.

Resource scheduling in large-scale, volatile desktop grids is challenging because resource state is both dynamic and eclectic. Matching available resources with requests is not always possible with existing approaches. Partial dissemination protocols, such as gossiping, may provide efficient schedules when resource requesters are located near providers that can meet their needs. However, when requesters are distant from available resources, regular information dissemination techniques can waste communication bandwidth with futile messages. Thus, it may be advantageous to attempt to advertise to select remote regions of the grid, without necessarily also going through all intermediate nodes. This paper proposes dissemination proxies to increase coverage footprints and reduce dissemination overhead. We incorporate selecting and adjusting the amount of proxy nodes into an adaptive dissemination algorithm, and show that dissemination proxies are able to reduce dissemination overhead, and handle available resource distribution scenarios where regular information dissemination approaches may not produce efficient protocols. We also report initial results that indicate that randomly selecting nodes to serve as proxies can perform as well as strategies that select seemingly better-qualified proxies.

Publish/subscribe model has become a prevalent paradigm for building distributed event delivering systems. Content-based publish/subscribe allows high expresses in subscriptions and thus is more appropriate for content dissemination. However, the scalability has remained a challenge in the design of distributed content-based publish/subscribe systems due to the expensive matching and delivering cost of content-based events. In this paper we propose an infrastructure built on top of distributed hash table for efficient content-based data distribution. Based on efficient subscription installation, event publication and event delivery mechanisms, the proposed infrastructure can simultaneously support any numbers of pub/sub schemas with different number of attributes. There are three key features in our design: (1) a locality-preserving hashing mechanism which partitions and maps the content space to nodes. Subscriptions and events are mapped to the corresponding node for efficiently matching; (2) an efficient event delivery algorithm which exploits the embedded trees in the underlying DHT to deliver events to the corresponding subscribers; (3) light-weighted load balancing mechanisms to adjust the load among peers and ensure that no peer is unduly loaded.

Effective scheduling in large-scale computational grids is challenging because it requires tracking the dynamic state of the large number of distributed resources that comprise the grid. Classical distributed information dissemination approaches such as push, pull, and their combinations, are not well suited to the problem of resource tracking, where resources are redundant and full information about all resources everywhere is neither necessary nor desirable. Aggregated, partial, or probabilistic forwarding protocols result in more efficient (but incomplete) dissemination, while maintaining sufficient information to enable effective scheduling. However, a static approach to dissemination in which all information is treated identically, is ineffective in the presence of spatial and temporal non-uniformity of resources and demands. For example, a single forwarding probability for gossipping-based dissemination may result in unnecessarily high overhead in some areas of the grid. Moreover, the right forwarding probability values can change over time, with changes in offered load and node utilization. Adaptive protocols can adjust the aggressiveness with which information is disseminated, based on current grid conditions, and can in turn increase query satisfaction rates, reduce overhead, or both. This paper explores the characteristics and behavior of adaptive probabilistic and change-sensitive information forwarding protocols, identifying and addressing several issues and problems, and introducing dissemination protocols that are better able to reduce overhead and increase query satisfaction rates for a variety of grid conditions.