Engagement
How does blended learning shape (dis-)engagement?
Open access · cc by · source: Europe PMC
In a disadvantaged upper-secondary school, blended learning both enabled and constrained engagement as teachers and students negotiated mismatched work paces.
Study at a glance
- Design
- Qualitative / archival — Five-month case study with observations in a disadvantaged upper-secondary blended school
- N
- N=32 · 32 year 10–12 students; 14 classroom observations
- Population
- Upper-secondary students and teachers in a blended-learning school
- Outcome
- Negotiated engagement/disengagement under digital tools and mismatched work paces
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Digital technologies were sometimes used to enhance learning and sometimes deliberately avoided. Teachers' observed work pace exceeded students' on average, producing tension when push to finish outstripped student pace. Engagement emerged as negotiated across blended context, teacher leadership, activity, and the student as learner.
Methodology
Over five months, researchers conducted a qualitative case study with classroom observations and participation from upper-secondary students and teachers in a blended-learning setting. They analysed how digital tools, teacher leadership, activity design, and learner self-beliefs shaped engagement and disengagement.
Limitations
A single-school case study cannot estimate average effects of blended learning nationwide. Observational pace ratings are interpretive, not randomised causal estimates of achievement gains.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
In blended and digital classrooms, engagement is co-produced by teachers and students: mismatched work paces and selective use or avoidance of digital tools can enable or constrain involvement.
Evidence for the claim as stated.
Some papers treat engagement mainly as an affective/participation survey outcome after an intervention; others treat engagement/disengagement as an ongoing negotiation in classroom practice — different grains of analysis.
Evidence for the claim as stated.
A five-month upper-secondary blended case used observation to analyse (dis)engagement. Digital tools were sometimes used to enhance learning and sometimes deliberately avoided. Teachers’ observed work pace exceeded students’ on average, producing tension. Engagement was negotiated across context, teacher leadership, activity and the student-as-learner — an interpretive case, not a national blended-learning effect.
Evidence for the claim as stated.
Help-seeking and belonging are not one theme. Live-chat students were overwhelmingly satisfied and treated chat as just-in-time academic access, especially fully online learners (91 vs 155 blended). Loneliness interviews and ableism themes describe exclusion, stigma and exam visuality. K–12 blended observation describes negotiated disengagement when teacher pace outstripped students. Positive tool themes and exclusion themes can both be accurate in different rooms.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Some papers treat engagement mainly as an affective/participation survey outcome after an intervention; others treat engagement/disengagement as an ongoing negotiation in classroom practice — different grains of analysis.
Help-seeking and belonging are not one theme. Live-chat students were overwhelmingly satisfied and treated chat as just-in-time academic access, especially fully online learners (91 vs 155 blended). Loneliness interviews and ableism themes describe exclusion, stigma and exam visuality. K–12 blended observation describes negotiated disengagement when teacher pace outstripped students. Positive tool themes and exclusion themes can both be accurate in different rooms.
Related papers in this topic
Same topic cluster — not a recommendation engine.