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The purpose of this paper is to present an analytical review of the educational innovation field in the USA. It outlines classification of innovations, discusses the hurdles to innovation, and offers ways to increase the scale and rate of innovation-based transformations in the education system.

The paper is based on a literature survey and author research.

US education badly needs effective innovations of scale that can help produce the needed high-quality learning outcomes across the system. The primary focus of educational innovations should be on teaching and learning theory and practice, as well as on the learner, parents, community, society, and its culture. Technology applications need a solid theoretical foundation based on purposeful, systemic research, and a sound pedagogy. One of the critical areas of research and innovation can be cost and time efficiency of the learning.

Several practical recommendations stem out of this paper: how to create a base for large-scale innovations and their implementation; how to increase effectiveness of technology innovations in education, particularly online learning; how to raise time and cost efficiency of education.

Innovations in education are regarded, along with the education system, within the context of a societal supersystem demonstrating their interrelations and interdependencies at all levels. Raising the quality and scale of innovations in education will positively affect education itself and benefit the whole society.

Originality is in the systemic approach to education and educational innovations, in offering a comprehensive classification of innovations; in exposing the hurdles to innovations, in new arguments about effectiveness of technology applications, and in time efficiency of education.

The purpose of this paper is to present an adaptation of a program that is at the intersection of two dynamic force fields. The first relates to imperatives impinging upon and inherent in higher education. The second ties to the concept of ecosystems as spaces for aligning actors and resources to create value.

Tables I-III present pre-test and post-test means and p-values for the paired sample t-tests for the measures.

As expected, post-test means are consistently significantly higher (or lower depending on item wording) for a shift in beliefs away from self-censoring and prejudging ideas during ideation and more toward greater openness in the ideation process.

The paper examines the outcome of an educational program.

This research explores the impact of the locally grown strategies for learning support, as a positive deviance (PD) study, during the COVID-19 pandemic in rural Uganda.

The researchers employed a randomized control trial (RCT) as an original design whereby 50 schools received a full package of SMS and WhatsApp peer groups of head teachers, 50 schools received SMS only and another 50 served as a control group. As an analytical method, this study adopted a difference-in-difference (DID) model to analyze the impact of the radio talk shows promoted through SMS followed by discussion among WhatsApp peer groups. The data collected in June 2021 and February 2022 were used due to the COVID-19-related data limitation of the baseline survey collected in 2019.

The authors found that the local radio talk shows as a PD intervention had a humble impact on preventing pupils’ dropout during the school closures for two years in Uganda. However, the authors did not obtain a significant result on the impact of the PD intervention on pedagogical support or learning outcomes at the school level. The authors also found that the pupils have significantly dropped their level of proficiencies in literacy and numeracy during the pandemic.

The findings could be of value for the leaders, educators and policymakers to understand the most recent update of learning situation in Uganda and the potential impact of locally grown strategies for learning which does not require external inputs.

Human resources (HR) management has encountered unforeseen obstacles and issues in recruiting, retaining, training and developing workforces under the “new normal” due to pandemic circumstances followed by the Russo–Ukrainian War and global economic turmoil. As the world is now well-equipped with technological advancements and internet-based connectivity, many pandemic disruptions have been avoided through rapid adaptation of technological systems. Despite the constructive outcomes of this contemporary approach to learning and development (L&D), this study explores the further depths of massive open online courses (MOOC) platform adoption in human resource development initiatives during pandemic times.

A qualitative research approach was adopted to understand the employee and HR perspective on the changes in L&D approaches in organizations. To gather the primary data, respondents were divided into two clusters; different sets of questionnaires were developed for interview sessions.

Results suggest that employee L&D was much more improvised with distance or online learning, including organizational e-learning systems and MOOC platforms. To accomplish their HR development goals, organizations went through significant transformations during the Coronavirus pandemic; organizational attempts to initiate online training and MOOC-based learning fostered positive results in employee capacity development, process improvement, employee engagement and motivation.

This research will assist organizations in developing interactive training methods as an effective replacement for traditional training. Additionally, it will assist readers, practitioners and HR specialists in understanding how MOOCs are changing the L&D ecosystem.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

This study aims to depict how a change laboratory (CL) promotes sustainable professional practice at the workplace to tackle unequal access to educational success.

The empirical findings are from a CL focusing on school professionals’ agency and a follow-up study one year after the CL.

The study shows how the staff gained insight that professional agency is a collective and relational practice. Furthermore, the staff explored how to make a difference with viable means to create new workplace models for students’ success despite experiencing a conundrum.

This study examined participants’ perspectives in workplace change and provided support for further research examining how professionally and collectively designed models gain sustainability in schools.

This study provides empirical data of how professional agency for change driven by collective visions can be accelerated with the interventionist method CL among school professionals.

This study emphasizes the value of professional collective learning at the workplace, driven by several professional groups in school, and the need to follow up to detect sustainable change.

This study emphasizes the value of professional collective learning at the workplace, driven by several professional groups in school, and the need to follow up to detect sustainable change.