Support provided for K-12 teachers teaching remotely with technology during emergencies: A systematic review - Crompton, Helen; Burke, Diane; Jordan, Katy; Wilson, Samuel (Journal of Research on Technology in Education, 2021)
Emergencies can cause disruption to education. This study is unique in providing the first empirical systematic review on teacher support for Emergency Remote Education (ERE) from 2010 to 2020. A total of 57 studies emerged from the PRISMA search. This mixed-method study used deductive and inductive iterative methods to examine the data. The data reveal teacher support strategies from across 50 different high and low-income countries. Few studies focused on a teacher’s subject and the age range taught. In the examination of professional development provided to prepare K-12 teachers to conduct ERE, eight codes emerged from the grounded coding as; 1) prior preparation, 2) understanding ERE, 3) needs analysis, 4) digital pedagogical strategies, 5) technology tools, 6) frameworks, 7) digital equity, and 8) mental wellness.
ZenodoArchiveID: 5652026 Publisher: Routledge _eprint: https://doi.org/10.1080/15391523.2021.1899877 KerkoCite.ItemAlsoKnownAs: 10.1080/15391523.2021.1899877 10.1111/bjet.13114 10.5281/zenodo.5652026 2339240:258WF4VH 2339240:RAP22KJU 2405685:5UAQ3N5K 2405685:BKMMRYCD 2405685:IA5XF32V 2405685:SU6FMBKT 2405685:XERPP4G9 2534379:UVB8PHFN
Keywords: COVID-19; Teacher education; _EdTechHub_Output; _GS:indexed; _MELA_seen; ___working_potential_duplicate; _cover:analysis:nopdf; _r:CopiedFromEvLib; _yl:a; disasters; emergencies; emergency remote education; pandemic; remote education

Learning with technology during emergencies: A systematic review of K-12 education - Crompton, Helen; Burke, Diane; Jordan, Katy; Wilson, Samuel W. G. (British Journal of Educational Technology, 2021)
Emergency situations that cause damage to educational buildings or require the closure of schools due to unsafe health, environmental, or political conditions can be an unwelcomed interruption to education. Indeed, the recent COVID-19 pandemic created the largest disruption of education in history, affecting 94% of the world's student population. In emergencies, technology is often utilised as part of a crisis response protocol by continuing education using emergency remote education (ERE). The purpose of this study is to determine how technology has been used to continue K-12 learning remotely during an emergency. This systematic review included an aggregated and configurative synthesis to examine extant empirical work over eleven years, from January 2010 to December 2020. Following a rigorous, PRISMA selection process, 60 articles were included in the final analysis from 48 countries. Grounded coding of the strategies used for learning revealed the following categories: communication, delivery systems, student ERE readiness, partnerships, promoting student learning and engagement, and resources. Grounded coding of the technologies revealed that types of technologies used were divided into two major categories: Internet-based and non-Internet based, with the majority using Internet-based technologies. Practitioner notes What is already known about this topic The COVID-19 pandemic has caused school closures across the globe and prevented in-person school teaching. The rapid shift to distance education in schools can be conceptualised as ‘emergency remote education’ (ERE). Prior ERE research focused on bounded geographic locations where localised emergencies occurred. What this paper adds This provides the scholarly community with a unique systematic review of existing academic research on K-12 ERE implementation in emergencies. This provides aggregated data and analysis on the past 11 years of the types of emergencies, participants, subject domain, technologies used, and location information. This provides findings of the types of remote teaching strategies involving technology used to continue K-12 learning in emergency situations. This provides a set of recommendations on ERE for teachers, school leaders, policy makers, and funders. This provides researchers with a review of the field with identification of gaps and future research opportunities. Implications for practice and/or policy Recommendations regarding ERE are provided in this paper that will be of benefit to K-12 teachers, school leaders policymakers, and funders in the continuing COVID-19 pandemic and future emergencies. The research gaps highlighted in this paper, such as the lack of studies conducted in low and low middle-income countries, are presented with suggestions for much needed future research. This can lead to changes in practice and policy.
ZenodoArchiveID: 5652042 _eprint: https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.13114 KerkoCite.ItemAlsoKnownAs: 10.1111/bjet.13114 10.5281/zenodo.5652042 2339240:ELI3E5RF 2339240:TJNJX997 2405685:3KJJW6XZ 2405685:9V69ZAFP 2405685:BDG6N6PJ 2405685:JE8I8566 2405685:YY7LXWQB
Keywords: COVID-19; _DOILIVE; _EdTechHub_Output; _MELA_seen; ___working_potential_duplicate; _yl:b; _zenodo:submitted; disasters; emergencies; emergency remote education; pandemic

Education during the COVID-19: crisis Opportunities and constraints of using EdTech in low-income countries - Jordan, Katy; David, Raluca; Phillips, Toby; Pellini, Arnaldo (Revista de Educación a Distancia (RED), 2021)
The Covid-19 pandemic has ushered in a period of educational disruption on an unprecedented scale. During this time of crisis, education will not be business as usual, and EdTech alone cannot close the learning gap. It will be dedicated teachers and resilient educators who will ensure learning doesn’t st op — but they could be helped by the right EdTech tools. However, the digital divide means that internet and mobile network access varies greatly in middle and low - income countries. In this discussion paper, we explore some of the key constraints of using EdTech at scale to support education in low - income countries at a time of crisis, and highlight the opportunities that have so far emerged, in a rapidly - changing context. We draw upon evidence and examples to inform policy and programming decisions, moving from the initial emergency response to building resilience in the longer term, and planning to diagnose and treat the learning gaps that have emerged during the crisis.
ZenodoArchiveID: 5652036 Dates: 13-11-2020 — Actualizado el 09-01-2021 KerkoCite.ItemAlsoKnownAs: 10.5281/zenodo.5652036 10.6018/red.453621 2405685:2BIQKP9C 2405685:IVHRNTQ7 2405685:L7Y5JD68 2405685:ZXQZ3FVV
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; ___working_potential_duplicate; _zenodo:submitted; países de bajos ingresos

The effectiveness of technology-supported personalised learning in low- and middle-income countries: A meta-analysis - Major, Louis; Francis, Gill A.; Tsapali, Maria (British Journal of Educational Technology, 2021)
Digital technology offers the potential to address educational challenges in resource-poor settings. This meta-analysis examines the impact of students' use of technology that personalises and adapts to learning level in low- and middle-income countries. Following a systematic search for research between 2007 and 2020, 16 randomised controlled trials were identified in five countries. Studies involved 53,029 learners aged 6–15 years. Coding examined learning domain (mathematics and literacy); personalisation level and delivery; technology use; and intervention duration and intensity. Overall, technology-supported personalised learning was found to have a statistically significant—if moderate—positive effect size of 0.18 on learning (p = 0.001). Meta-regression reveals how more personalised approaches which adapt or adjust to learners' level led to significantly greater impact (an effect size of 0.35) than those only linking to learners' interests or providing personalised feedback, support, and/or assessment. Avenues for future research include investigating cost implications, optimum programme length, and teachers' role in making personalised learning with technology effective. Practitioner notes What is already known about this topic? Promoting personalised learning is an established aim of educators. Using technology to support personalised learning in low- and middle-income countries (LMICs) could play an important role in ensuring more inclusive and equitable access to education, particularly in the aftermath of COVID-19. There is currently no rigorous overview of evidence on the effectiveness of using technology to enable personalised learning in LMICs. What this paper adds? The meta-analysis is the first to evaluate the effectiveness of technology-supported personalised learning in improving learning outcomes for school-aged children in LMICs. Technology-supported personalised learning has a statistically significant, positive effect on learning outcomes. Interventions are similarly effective for mathematics and literacy and whether or not teachers also have an active role in the personalisation. Personalised approaches that adapt or adjust to the learner led to significantly greater impact, although whether these warrant the additional investment likely necessary for implementation at scale needs to be investigated. Personalised technology implementation of moderate duration and intensity had similar positive effects to that of stronger duration and intensity, although further research is needed to confirm this. Implications for practice and/or policy: The inclusion of more adaptive personalisation features in technology-assisted learning environments can lead to greater learning gains. Personalised technology approaches featuring moderate personalisation may also yield learning rewards. While it is not known whether personalised technology can be scaled in a cost-effective and contextually appropriate way, there are indications that this is possible. The appropriateness of teachers integrating personalised approaches in their practice should be explored given ‘supplementary’ uses of personalised technology (ie, additional sessions involving technology outside of regular instruction) are common.
Archive: https://zenodo.org/record/4817787 KerkoCite.ItemAlsoKnownAs: 10.1111/bjet.13116 10/gj6k5n 2339240:382K6GCA 2339240:53R3ZYT5 2339240:CYQPAERV 2339240:EXFAZMDQ 2339240:P2I2EU98 2339240:RM59PWFE 2405685:5U948655 2405685:FIXCCB5I 2405685:HBGSTQ7X 2405685:QFTDGH3C 2405685:RZNJVMWH 2405685:V8UFGT52 2405685:WTT4UQ43 2405685:ZD4YGMMJ 4042040:G8KVDVSC
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:analysis:nopdf; _zenodo:submitted; computer-assisted learning; learning outcomes; low- and middle-income; meta-analysis; personalisation; personalised adaptive learning; ⛔ No DOI found