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1. Software Training in HEP

   Sudhir Malik, Samuel Meehan (February 2021, ArXivorg)

   null (Ed.)

   Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g. Unix, version control,C++, continuous integration). The second is knowledge of domain specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving more specialized techniques. These include parallel programming, machine learning and data science tools, and techniques to preserve software projects at all scales. This paper dis-cusses the collective software training program in HEP and its activities led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients from which solutions to the computing challenges of HEP can be formed. Beyond serving the community by ensuring that members are able to pursue research goals, this program serves individuals by providing intellectual capital and transferable skills that are becoming increasingly important to careers in the realm of software and computing, whether inside or outside HEP 

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2. Software Training in HEP

   Sudhir Malik, Samuel Meehan (February 2021, ArXivorg)

   null (Ed.)

   Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g. Unix, version control,C++, continuous integration). The second is knowledge of domain specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving more specialized techniques. These include parallel programming, machine learning and data science tools, and techniques to preserve software projects at all scales. This paper dis-cusses the collective software training program in HEP and its activities led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients from which solutions to the computing challenges of HEP can be formed. Beyond serving the community by ensuring that members are able to pursue research goals, this program serves individuals by providing intellectual capital and transferable skills that are becoming increasingly important to careers in the realm of software and computing, whether inside or outside HEP 

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3. Understanding the Nature and Evolution of Sustainability Mindset in First-Year Engineering Students

   Colon, Krystal; Rivera_Castro, Andrea K; Santiago_Roman, Aidsa I; Papadopoulos, C; Dika, Sandra L; Santiago, Nayda G; Alicea_Romero, Kaishmarie (June 2024, ASEE Conferences)

   This article reviews the notion of a Sustainability Mindset in comparison to sustainability competencies in the context of a study of a first year cohort of students beginning a minor in Sustainability Engineering at the University of Puerto Rico, Mayagüez. A framework of Knowledge (K), Skills (S), Attitudes (A), Behaviors (B), and Attitudes (A) is adopted to capture the students' developing mindsets broadly the context of Sustainability. A detailed open-form survey was administered after the first semester and was completed by 9/11 participants. Results show mature growth in the domain of sustainability (e.g., broad knowledge of the concept of sustainability to encompass the three 'pillars' of environmental, equity, and economic factors, and deep knowledge regarding ideas such as circular economy and earth systems cycles). Further growth is also demonstrated in academic and personal development (e.g., improved study skills, time management, and research skills). Future work will endeavor to continue observing the evolution of the mindset at the KSBA level and at finer levels of detail. 

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4. Training the Next Generation of Seismologists: Delivering Research-Grade Software Education for Cloud and HPC Computing Through Diverse Training Modalities

   https://doi.org/10.1785/0220240413  

   Denolle, Marine A; Tape, Carl; Bozdağ, Ebru; Wang, Yinzhi; Waldhauser, Felix; Gabriel, Alice-Agnes; Braunmiller, Jochen; Chow, Bryant; Ding, Liang; Feng, Kuan-Fu; et al (June 2025, Seismological Research Letters)

   Abstract With the rise of data volume and computing power, seismological research requires more advanced skills in data processing, numerical methods, and parallel computing. We present the experience of conducting training workshops in various forms of delivery to support the adoption of large-scale high-performance computing (HPC) and cloud computing, advancing seismological research. The seismological foci were on earthquake source parameter estimation in catalogs, forward and adjoint wavefield simulations in 2D and 3D at local, regional, and global scales, earthquake dynamics, ambient noise seismology, and machine learning. This contribution describes the series of workshops delivered as part of research projects, the learning outcomes for participants, and lessons learned by the instructors. Our curriculum was grounded on open and reproducible science, large-scale scientific computing and data mining, and computing infrastructure (access and usage) for HPC and the cloud. We also describe the types of teaching materials that have proven beneficial to the instruction and the sustainability of the program. We propose guidelines to deliver future workshops on these topics. 

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5. PCEX: Interactive Program Construction Examples for Learning Programming

   https://doi.org/10.1145/3279720.3279726  

   Hosseini, Roya; Akhuseyinoglu, Kamil; Petersen, Andrew; Schunn, Christian D.; Brusilovsky, Peter (January 2018, 18th Koli Calling International Conference on Computing Education Research)

   A sizable body of research on instructional practices supports the use of worked examples for acquiring cognitive skills in domains such as mathematics and physics. Although examples are also important in the domain of programming, existing research on programming examples is limited. Program examples are used by instructors to achieve two important goals: to explain program behavior and to demonstrate program construction patterns. Program behavior examples are used to demonstrate the semantics of various program constructs (i.e., what is happening inside a program or an algorithm when it is executed). Program construction examples illustrate how to construct a program that achieves a specific purpose. While both functions of program examples are important for learning, most of the example-focused research in computer science education focused on technologies for augmenting program behavior examples such as program visualization, tracing tables, etc. In contrast, advanced technologies for presenting program construction examples were rarely explored. This work introduces interactive Program Construction Examples (PCEX) to begin a systematic exploration of worked-out program construction examples in the domain of computer science education. A classroom evaluation and analysis of the survey data demonstrated that the usage of PCEX examples is associated with better student's learning and performance. 

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