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Measuring Processing Strategies: Perspectives for Eye Tracking and fMRI in Multi-method Designs

Many educational researchers argue that the main aims of educational research are understanding and enhancing the quality of learning and processing (Dinsmore, 2017; Vermunt & Donche, 2017) and researchers are therefore looking for appropriate methods in order to capture students’ learning and processing. Until now, empirical research on students’ processing strategies in higher education has mostly focused on the use of self-report measures (Dinsmore & Alexander, 2012; Fryer, 2017; Vermunt & Donche, 2017). In early work on students’ processing strategies during learning from texts, interviews were used (Marton & Saljd, 1976) and, later on, concurrent think-aloud protocols (Fox, 2009; Pressley & Afflerbach, 1995). Following this early work, self-report questionnaires were used to gain insight into students’ general disposition towards processing strategies (Biggs, 1987, 1993; Entwistle & Waterston, 1988; Vermunt, this volume). There has thus been a shift from measuring processing strategies at a task-specific level to measuring students’ general disposition towards processing strategies. Researchers in the field agree on the variability of processing strategies over learning tasks, but most empirical research is conducted at a more general level, thus ignoring this variability at the task level (Fryer, 2017; Vermunt & Donche, 2017).

More recently, with the advent of new psychophysiological measures, such as eye-tracking and functional magnetic resonance imaging (fMRI), there is a renewed interest in examining the task-specific processing strategies during a learning task. These online measures can be used during the execution of a learning task and are able to capture both conscious and unconscious processing activities. The advantage of these psychophysiological measures is that subjects cannot consciously manipulate their responses in comparison with self-report measures where this could be happening (Dimoka et al., 2012) and that they can register the micro-processes of learning (e.g., how information is integrated between words and sentences). As will be demonstrated later in this chapter, some micro-measures are more strategic and conscious in nature than other micro-measures. Self-report measures are only able to capture these strategic and conscious processes, while psychophysiological measures can capture both strategic and more automatized processes during learning.

In this chapter, we will give an overview on how eye tracking and fMRI can be used to examine students’ processing strategies in relation to learning from verbal material (i.e., words, paragraphs and texts). We will discuss the opportunities of these measures and show what they can and cannot tell us about processing strategies. In addition, the challenges will be discussed of using these psychophysiological measures in relation to processing strategies. In a final step, we will give our view on how this field can move forward and what we can take away from this chapter.


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