Warren Buckland's research interests:
(1) Film Theory (semiotics, cognitive film theory);
(2) Narrative Theory (puzzle films, unreliable narration);
(3) Digital Humanities (statistical style analysis, stylometric analysis of screenplays).
My approach to teaching mixes three overlapping styles: deep learning, integration of theoretical and practical knowledge, and hands-on experience.
Deep learning is based on the close reading of texts (both academic and film texts).
Bridging theory/practice makes film studies a more relevant discipline, due to the type of knowledge it generates.
Humanities Computing is taught in a computer lab and focuses on big data and distant reading.
Deep learning attempts to avoid surface learning (a broad, sweeping, superficial survey of huge amounts of information).
The core of a pedagogy that integrates film theory and film practice consists of the shot-by-shot analysis of film sequences in order to study what Vlada Petric calls 'cinematic strategy' - a filmmaker's shooting procedures and methods.
Humanities Computing is taught via practical activities such as the statistical analysis of box office figures; the statistical analysis of film style; and the data mining of big data - including film reviews, Twitter, and screenplays.