ABSTRACT
Amidst COVID-19, teacher education has shifted to online learning. Although much is known about digital inequity in routine times, little is known about it under constrained conditions, particularly among women of minority groups. The study's goal was to explore the online-learning challenges encountered by (minority) Bedouin female preservice teachers (n = 41) compared to those encountered by (majority) Jewish counterparts (n = 60). Data from reflections (N = 101), focus groups (2), and (68) interviews underwent qualitative-constructivist content analysis. Group comparisons revealed socioculturally-based differential learning pathways, leading to educational inequities. We discuss possible ways to ensure equitable online teacher education using the "digital divide" perspective.
ABSTRACT
Using mobile learning (ML) has become exceedingly relevant in times of distant teaching. Although much is known about the factors affecting ML usage, less is known about the ML adoption process under constraints such as the COVID-19 pandemic. The aim of this exploratory case study was to gain insight into the ML adoption process using the lens of Rogers' Diffusion of Innovation Theory. Participants were in-service (32) and preservice (29) teachers who attended ML training. Data were collected using semi-structured interviews (20), focus groups (6), and participants' reflections (183) at three time points. Data underwent multilevel analysis (content and linguistic analysis), revealing 12 themes that denote the ML adoption process and demonstrated intergroup similarities and differences. The study provides theoretical insight into the ML adoption process under crisis and highlights the features that must be addressed to promote optimal ML adoption in teacher education in both routine and emergency conditions.
