33 research outputs found
The association of eye movements and performance accuracy in a novel sight-reading task
The present study investigated how eye movements were associated with performance accuracy during sight-reading. Participants performed a complex span task in which sequences of single quarter note symbols that either enabled chunking or did not enable chunking were presented for subsequent serial recall. In between the presentation of each note, participants sight-read a notated melody on an electric piano in the tempo of 70 bpm. All melodies were unique but contained four types of note pairs: eighth-eighth, eighth-quarter, quarter-eighth, quarter-quarter. Analyses revealed that reading with fewer fixations was associated with a more accurate note onset. Fewer fixations might be advantageous for sight-reading as fewer saccades have to be planned and less information has to be integrated. Moreover, the quarter-quarter note pair was read with a larger number of fixations and the eighth-quarter note pair was read with a longer gaze duration. This suggests that when rhythm is processed, additional beats might trigger re-fixations and unconventional rhythmical patterns might trigger longer gazes. Neither recall accuracy nor chunking processes were found to explain additional variance in the eye movement data
A new view on complex span tasks. Using eye tracking to reveal the influence of memory load on eye movements
Visual processing tasks, such as reading, involve the perception of visual symbols with series of fixations, their short-term storage and decoding. For fluent processing in such a task, the ability to perceive multiple symbols with single fixations is crucial. As of yet, it is an unresolved question how this ability is influenced by memory load. I expect that limited attentional resources are used to ensure a high perceptual capacity of fixations. Hence, the amount of information that can be perceived with a single fixation should decrease with increasing memory load. I employed a novel combination of the complex span paradigm and eye tracking to test this assumption. Music students (n=75) were asked to memorize one note and then play a simple melody at first sight on a piano. After twelve repetitions of this procedure, they were asked to recall the memorized notes in correct order. Eye movements during the performance of the melodies were tracked. While the distance of saccades was unaffected by memory load, the number of fixations used to read the melodies increased with each additional note that had to be held in memory. When more notes were stored in immediate memory, fewer attentional resources were available for visual processing and the amount of information that was perceived with a single fixation decreased. These findings show that the combination of complex span tasks and tracking of eye movements are the ideal research method to analyze the influence of memory load on eye movements during visual processing
The magic numbers 4 and 7. Modeling chunking in immediate memory
The main assumption of chunking theory is that knowledge about semantic units in a certain task domain can be used to compress incoming information. Although the maximal capacity of immediate memory is 4±1 information units, this information compression allows to enlarge the memory capacity by increasing the size of information units. As even random information can be compressed to a certain extent, a capacity limit of 7 single bits of information is typically found with random material. These assumptions were tested with a complex span task. Expert musicians (n=75) memorized the pitch of a single note and then played a simple melody on a piano at first sight. This procedure was repeated twelve times and then a memory test followed in which all memorized notes had to be recalled in correct order. The presence of semantic units was varied within-participants: in experimental trials, consecutive notes formed major chords, while in control trials they did not. As expected, mixed model analyses revealed that memory capacity was larger when the material contained semantic units. In experimental trials, the capacity limit was 3.18 chords while in control trials it was 7.32 single notes. The TBRS*C computational model integrates time-based decay, refreshing mechanisms and chunking. It is explicitly suited to model recall performance in complex span tasks. This model will be used to analyze the data in order to confirm its validity
Corona und die Digitalisierung der universitÀren Lehre an der UniversitÀt Mannheim : Executive Summary zu einer Studierendenbefragung im HWS 2020/21
Die Corona-Pandemie und die MaĂnahmen zu deren EindĂ€mmung haben dazu gefĂŒhrt, dass die UniversitĂ€t Mannheim ihren Lehrbetrieb in kĂŒrzester Zeit grundlegend umstellen musste. Notgedrungen musste auf PrĂ€senzveranstaltungen verzichtet und die Nutzung digitaler Mittel ausgebaut werden. Um Informationen ĂŒber diese Umstellung zu sammeln, fĂŒhrte das QualitĂ€tsmanagement der UniversitĂ€t Mannheim eine Befragung unter Studierenden zum HWS 2020/21 durch. Diese Befragung sollte Einblicke in die Perspektive der Studierenden geben und zeigen, wie sie die Lehre in diesem Semester bewerten
Chunking in tonal contexts: Information compression during serial recall of visually presented musical notes
C Dur. Chunking im GedÀchtnis von Musikexperten
Theoretical background: Chunking is a memory strategy performed by experts that allows them to increase their memory capacity for information from their task domain by strategically grouping single pieces of information into known units. In task domains, such as music, certain combinations of pieces of information form frequently reoccurring units. For example, the three notes C â E â G form a unit labeled âC major chordâ. Expert musiciansâ long-term memory contains this combination of notes and the label for it. If these three notes have to be memorized, experts can mentally represent them using the associated label. As a consequence, encoding and maintenance processes become more effective and more information can be stored and successfully recalled. In short, chunking is a process that uses knowledge for information compression in memory. I tested these assumptions in three experiments.
Method: Study 1 and study 2 used a serial recall task. Single note symbols were shown on a computer screen. They were presented sequentially for one second with a 500 ms inter-stimulus interval. Each note was presented at the same location than the previous one. Afterwards, the pitch of all notes had to be recalled in correct serial order. In study 1 (n = 88) 6 or 9 notes had to be recalled. It was varied within-participants if subsequent notes formed major chords or nonsensical sequences. In study 2 (n = 97) 4 or 8 notes had to be recalled. it was varied if subsequent notes formed cadences or nonsensical sequences. I used the GOLD-MSI questionnaire in both experiments. It provided an indicator of musical expertise which allowed to study the influence of musical expertise on recall performance.
Results: The data showed that experts had a higher recall accuracy than non-experts and there was a better recall accuracy when notes formed chords or cadences. In study 1, I found an interaction: There was a larger difference between the chords and the no-chords condition if participants had a high musical expertise.
Method: Study 3 used a complex span task. Participants were music students (n = 75). They were asked to memorize the pitch of a single, printed note and then perform a short, simple melody on a piano at first sight. This procedure was repeated and then, a memory test followed in which all memorized pitches had to be recalled in correct serial order. Again, it was manipulated if subsequent notes formed major chords or nonsensical sequences.
Results: I found a strong effect of the factor chords. Participant had a much larger recall accuracy if notes formed chords than when they did not. Currently, data collection for a fourth study is running, using the same complex span task with non-experts. This will make it possible to perform an expertise comparison in this paradigm as well. All in all, the data support the notion of chunking as a memory strategy of experts that leads to an increased memory capacity for domain-specific information
The interplay of eye movements and long-term memory: Using a novel combination of eye tracking and complex span tasks to reveal how eye movements draw on long-term memory
Studies comparing experts and novices have shown that eye movements during domain-specific visual processing, such as the reading of notated music, are supported by long-term memory (LTM). Accordingly, if long-term memory information that is irrelevant for the visual processing task is activated, LTM support of eye movements is impeded. As a result, the amount of information that can be perceived with a single fixation decreases and the number of fixations increases given limited reading time.
I employed a novel combination of the complex span paradigm and eye tracking to test this assumption. Music students (n=75) were asked to memorize one note and then to play an unknown, simple melody on a piano. After twelve repetitions of this procedure, they were asked to recall the memorized notes in correct order. It was varied within participants if successive memory notes formed chords or did not form chords. Eye movements during the musical performance of the melodies were tracked and memory performance was measured with a recall test.
When memory notes formed chords, recall accuracy was higher and eye movements showed more fixations. Moreover, the number of fixations increased with each additional note that had to be held in memory. Both the more efficient storage of information when memory notes formed chords and the encoding of additional notes in the course of one trial led to more task-irrelevant activation in LTM. This, in turn, hindered LTM support for the eye movements and led to reading with more fixations