Effects of multitasking on short-term learning
Bowman, Levine, Waite, & Gendron (2010) asked students to reply to instant messages while reading an academic journal article online. Comprehension was not affected but students took longer to read the article (even subtracting the time they were messaging), suggesting that they were switching between tasks and that task switching had a time-cost.
Where learning is not self-paced, multitasking has a cognitive cost, as in any demanding dual task situation (e.g. Gherri and Eimer 2010). Sana, Weston, and Cepeda (2013) found that students who multitasked on laptops during lectures understood significantly less of the lecture.
Even the opportunity to multitask may have a detrimental effect. Fries and Dietz (2007) asked 16 year old students to learn about medicine for a test. Some watched pleasurable short music video clips beforehand, while others were told they had to wait until later. The students who watched all the videos beforehand had a deeper comprehension of the medical information, suggesting that anticipation of a more pleasurable task caused distraction or reduced motivation. This would be consistent with Muraven and Baumeister's (2000) theory that there is a limited resource for attentional self control and resisting temptation depletes this resource. However there may also be a cost for giving in to temptation. Leroy (2009) found that people who were made to switch to a new task before finishing the first experienced an 'attentional residue' where thoughts of the first task diminished performance on the new activity.
Adler and Benbunan-Fich (2013) observed that people chose to multitask more when in a negative mood, and that this correlated with poorer performance. Multitasking can therefore be a type of procrastination and opposite to flow (Cziksentmihalyi, 1998). Further evidence linking poor motivation and multitasking was found by Calderwood, Ackerman and Conklin (2014). They used monitoring devices to observe students studying. Students who were more motivated spent less time off-task.
To see how people allocate time across tasks, Adler and Benbunan-Fich (2012) gave people 6 problem-solving tasks of various difficulty levels and types (e.g. sudoku) to solve in a fixed time. The more times people switched between tasks, the more mistakes they made, however medium multitaskers solved more problems.
Where learning is not self-paced, multitasking has a cognitive cost, as in any demanding dual task situation (e.g. Gherri and Eimer 2010). Sana, Weston, and Cepeda (2013) found that students who multitasked on laptops during lectures understood significantly less of the lecture.
Even the opportunity to multitask may have a detrimental effect. Fries and Dietz (2007) asked 16 year old students to learn about medicine for a test. Some watched pleasurable short music video clips beforehand, while others were told they had to wait until later. The students who watched all the videos beforehand had a deeper comprehension of the medical information, suggesting that anticipation of a more pleasurable task caused distraction or reduced motivation. This would be consistent with Muraven and Baumeister's (2000) theory that there is a limited resource for attentional self control and resisting temptation depletes this resource. However there may also be a cost for giving in to temptation. Leroy (2009) found that people who were made to switch to a new task before finishing the first experienced an 'attentional residue' where thoughts of the first task diminished performance on the new activity.
Adler and Benbunan-Fich (2013) observed that people chose to multitask more when in a negative mood, and that this correlated with poorer performance. Multitasking can therefore be a type of procrastination and opposite to flow (Cziksentmihalyi, 1998). Further evidence linking poor motivation and multitasking was found by Calderwood, Ackerman and Conklin (2014). They used monitoring devices to observe students studying. Students who were more motivated spent less time off-task.
To see how people allocate time across tasks, Adler and Benbunan-Fich (2012) gave people 6 problem-solving tasks of various difficulty levels and types (e.g. sudoku) to solve in a fixed time. The more times people switched between tasks, the more mistakes they made, however medium multitaskers solved more problems.
Adler and Benbunan-Fich suggested that task-switching increased arousal (decreasing boredom), giving a boost to motivation, however switching between tasks too often taxed memory, resulting in a net loss of efficiency. The effect of task-switching on arousal was detected using physiological measures by Yeykelis, Cummings, & Reeves (2014). They saw a jump in arousal when students switched activities.
In sum, multitasking costs time rather than saving it, and if students multitask while studying they learn less. The prevalence of multitasking among students may be due to attractiveness of the distractions offered by technology, particularly when competing with a less attractive study task. Anticipation of switching to a pleasant activity increases arousal but probably decreases cognitive effort on the current task, giving a boost to the new activity instead.
One criticism of these studies is that they only measured immediate learning, rather than long-term learning. The 'desirable difficulties' literature shows that gains may not show up in the short term, so it is important to look at the long term effects of multitasking.
One criticism of these studies is that they only measured immediate learning, rather than long-term learning. The 'desirable difficulties' literature shows that gains may not show up in the short term, so it is important to look at the long term effects of multitasking.