What is Dialogic Education

Regardless of the imperatives of the COVID-19 pandemic and the increasing adoption of artificial intelligence (AI) in higher education to meet learning outcomes, little is known about its integration in dialogic learning outcomes in the post-COVID 19 era. From the learning sciences perspective, this chapter explores faculty members' adoption of AI resources for dialogic pedagogy using a participatory research design and social-constructivism theory. Interview data was obtained from 6 faculty members of two of Ghana's teacher education universities. Manual coding in Microsoft Excel yielded themes from the participants' narrative data with voices embedded. The results suggest that generic computer training, social media and internet exposure, data analytics, multimedia capacity, and digital pedagogy are the leading skills required for AI integration for dialogic learning goals among faculty members. In conclusion, capacity building for faculty to effectively deploy AI resources in students' dialogic learning goals requires learning scientists' effort and inputs.