Institutional influences on the use of blended learning approach among Bachelor of Education students in selected public universities in Kenya

Abstract

Blended Learning has undisputedly proved to deliver quality education ‘anywhere’ and ‘anytime.’ However, these advantages are minimally tapped by many universities in Kenya. This study aims to assess the institutional on the implementation of blended learning as an approach for teaching and learning among Bachelor of Education students in selected public universities in Kenya. The research objectives were to establish the influence of learners’ characteristics, lecturers’ characteristics, and institutional preparedness on the use of blended learning for teaching and learning; and to develop a pedagogical model that explain institutional characteristics that influence the usage of blended learning for teaching and learning in public universities in Kenya. The study is grounded on Bandura’s Social Learning Theory. Learning, according to Bandura’s theory, is by looking, imitating, and modeling which are functions of motivation, self- efficacy, wellbeing, reinforcement or reward, and environment. This research used Pragmatism paradigm and exploratory sequential mixed research design to harvest actionable and relevant knowledge that solve the problem of low uptake of blended learning in public universities. Third-year bachelor of education students (N=6655), lecturers (N=218), heads of departments (N=8), and deans (N=8) in public universities in Kenya form the study population. The researcher used various sampling techniques because of the multiple sources of data (students, lecturers, and heads of department). Multiple-stage sampling and the Nassiuma formula were used to select 3 rd -year education students (n=218) and lecturers (n=49). Universities (n= 8) and heads of departments (n=8) were chosen using purposive sampling. In order to mine data on institutional preparedness and blended learning in public universities, semi-structured questionnaires were used on students and lecturers. Interview guides were used on heads of departments and observation checklists for direct observation of infrastructure. Sequentially, the quantitative inferences were aligned to qualitative inferences alongside desk review findings. Data was descriptively analyzed in the form of frequencies, percentages, mean, and standard deviation. Structural Equation Modeling helped in path analysis facilitated by Amos version 24. Qualitative data was analyzed using content analysis techniques. The technique involved transcription and data coding using excel. The researcher drew meaning and structures of the transcribed data with objectivity which were clustered under relevant themes and research questions. The study found that students positively accepted the use of blended learning (M=5.08, SD=2.03), and lectures weakly supported blended learning M=4.7, SD=1.87. About institutions, participants weakly agreed that universities had a conducive social learning environment for blended learning (M=4.82, SD= 1). On the pedagogical model, the study discovered three significant paths: University preparedness and students’ perception (regression estimate = .399; P>.05; University preparedness and students’ self-efficacy (regression estimates = .389; P>.05); and blended learning adoption and students’ perception (regression estimates = .55; P>.05). Students and lecturers responded that “Poor internet connection,” and “Lack of appropriate infrastructure and equipment,” as the main barriers. In conclusion, blended learning was an indispensable approach for 21 st -century classrooms and universities’ preparedness was crucial for its full implementation. The study recommended that students should undertake ICT skills training courses in the first year first semester; lecturers should be motivated and public universities create effective infrastructure, and policies and retool the faculty members. Further studies should be done on the use of Blended learning in private universities and secondary schools. The findings will help the university councils to create policies on blended learning and the Government of Kenya to adequately invest in ICT infrastructure in public universities.