Differences in performance on comprehension tests and learning efficiency were examined across conditions.
Machine-learning techniques have also been explored as a means to predict student performance and comprehension.
An extensive body of literature supports the effectiveness of active learning over traditional lectures for student exam performance and comprehension.
These negative effects on academics were demonstrated with varied outcomes test performance, grades, comprehension, recall, and note-taking.
However, such computational support focuses mainly on improving performance of comprehension tasks through problem posing, such as understanding domain knowledge or procedures in problem solving.
Besides, they evaluated their writing performance and comprehension through rereading instruction, revising, reviewing notes, and editing in all stages of their writing.
Laptop use negatively related to multiple learning outcomes including course grade, focus on lectures, reported clarity of lectures, exam performance, and comprehension (Fried, 2008; Kraushaar & Novak, 2010; Wood et al., 2012; Zhang, 2015).
External distractors such as ringing cell phones and irrelevant speech have consistently been shown to reduce performance on comprehension tests for material learned in the presence of the distractors (e.g., Banbury & Berry, 1998; Shelton et al., 2009; Sörqvist et al. 2010; Zeamer & Fox Tree, 2013).
More developed levels of vocabulary knowledge enable learners to read with less effort (Segalowitz & Segalowitz, 1993; Segalowitz, Segalowitz & Wood, Segalowitz, Segalowitz & Wood, ; Segalowitz, Segalowitz & Wood,1998) and result in better performance on comprehension tests (Chen, 2011; Miller & Peleg, 2010; Nassaji, 2003; Qian, 1999).
The study was approved by the Cambridgeshire Local NHS Research Ethics NRES Committeeee.> -wrap-foot> In the BDAE, higher scores indicate better performance: Auditory Comprehension (maximal score: 90), Syntactic Processing (maximal score: 32), Boston Naming Test (maximal score: 60).
One way of addressing these critical issues is to selectively disrupt neural processing in either of these 2 components of semantic cognition (IFG, pMTG) and examine performance on comprehension tasks requiring different degrees of semantic control.
