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However, key questions remain about what the characteristics are for effective CPD in this context. Through the presentation of existing literature and the qualitative analysis of interviews with 32 employees from 13 English colleges (n = 14 computer science lecturers, 10 course leaders, and 8 members of senior leadership) this article answers the following question: \u2018What are the characteristics of effective continuing professional development for computer science teachers in the 16-18 sector?\u2019 Existing literature indicates how CPD benefits from: (1) knowledge development and application to classroom teaching, (2) self-efficacy development and measurement, (3) observation, feedback and reflection, (4) collaboration and communities of practice, (5) sufficient time, and (6) institution support. Meanwhile, the thematic analysis of interview data led to the creation of five overarching themes: (1) computer science CPD should address various knowledge domains, (2) CPD requires institutional support, (3) CPD should be engaging, (4) computer science CPD should involve a combination of activities, and (5) CPD should be measurable. This qualitative article also presents interview excerpts and contributes to computing education research and practice by presenting a set of thirty guidelines which outlines the characteristics of effective CPD in the context of computer science teachers in the 16-18 sector. These guidelines could be beneficial for both CPD providers and educators in ensuring CPD opportunities are designed more effectively, and with an understanding of both parties\u2019 needs.<\/jats:p>","DOI":"10.1145\/3582275","type":"journal-article","created":{"date-parts":[[2023,1,30]],"date-time":"2023-01-30T11:55:16Z","timestamp":1675079716000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Classifying the Characteristics of Effective Continuing Professional Development (CPD) for Computer Science Teachers in the 16-18 Sector"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8513-4646","authenticated-orcid":false,"given":"Jordan","family":"Allison","sequence":"first","affiliation":[{"name":"University of Gloucestershire"}]}],"member":"320","published-online":{"date-parts":[[2023,6,8]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/CSCI51800.2020.00168","volume-title":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","author":"Allison Jordan","year":"2020","unstructured":"Jordan Allison. 2020. 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