FAM: Ein Fragebogen zur Erfassung aktuller Motivation in Lern- und Leistungssituationen

Rheinberg, Falko; Vollmeyer, Regina; Burns, Bruce D.

doi:10.1026//0012-1924.47.2.57

Cited by 290 publications

(144 citation statements)

References 8 publications

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“…Some other studies used the Questionnaire for Current Achievement Motivation assessing interest, subjective probability of success, challenge, and anxiety (Rheinberg, Vollmeyer, & Burns, 2001); it was found that current achievement motivation predicted performance on tests measuring general mental ability, knowledge acquisition, and complex problem solving (e.g., Freund & Holling, 2011;Vollmeyer & Rheinberg, 2000, 2006. It can be concluded from these results that current test motivation plays an important role in ability test performance, and poor test performance in a low-stakes setting cannot unambiguously be attributed to low ability alone (see Duckworth et al, 2011;Steinmayr et al, 2014).…”

Section: Current Test Motivation In Intelligence Testingmentioning

confidence: 99%

The relation over time between achievement motivation and intelligence in young elementary school children: A latent cross-lagged analysis

Bergold

Steinmayr

2016

Contemporary Educational Psychology

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Section: Current Test Motivation In Intelligence Testingmentioning

confidence: 99%

The relation over time between achievement motivation and intelligence in young elementary school children: A latent cross-lagged analysis

Bergold

Steinmayr

2016

Contemporary Educational Psychology

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“…Whereas this measurement procedure is meant to grasp cognitive load, another very similar measurement procedure is meant to grasp motivation. An example is given by Rheinberg et al (2001) who developed the questionnaire of actual motivation (QAM), which includes nearly the same kind of questions.…”

Section: Cognitive and Motivational Resourcesmentioning

confidence: 99%

Reanalyzing the expertise reversal effect

Schnotz

2009

Instr Sci

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Finding the best match between learners' expertise and instruction is a central issue in educational psychology. The idea that different learners might need different instruction gave rise to the concept of aptitude-treatment interaction (ATI) launched by Cronbach and Snow (1977). The expertise reversal effect is a variant of an ATI effect. It occurs, when an instructional format that is beneficial for novices compared to other formats looses its advantage with increasing expertise of the learners and finally becomes disadvantageous for individuals with higher expertise (Kalyuga et al. 2003).Expertise reversal effects have been found for example by Kalyuga et al. (1998Kalyuga et al. ( , 2000Kalyuga et al. ( , 2001aKalyuga et al. ( , b, 2003, Leahy et al. (2003). The contributions of this special issue further elaborate these findings. Oksa, Kalyuga, and Chandler (this issue) demonstrate that the expertise reversal effect can be found not only in well-structured, but also in ill-structured domains such as the interpretation of literacy. Nückles, Hübner, Dümer, and Renkl (this issue) show that the expertise reversal effect has also motivational aspects and applies to the use of strategies. The article of Homer and Plass (this issue) indicates that the effect is not only related to domain-specific prior knowledge, but also to the general developmental level of learners. The findings of Blayney, Kalyuga, and Sweller (this issue) argue for the importance of adapting learning environments to the changing levels of learner expertise in the use of spreadsheets. Finally, Salden, Aleven, Schwonke, and Renkl (this issue) address the question of balance between providing sufficient instructional assistance on the one hand and self-regulated generative learning on the other hand in the case of worked examples, and they demonstrate that adaptive fading of instructional assistance is crucial for effective learning.There are some fundamental assumptions that can be found throughout the contributions of this special issue and in other papers on cognitive load theory. One assumption is that cognitive load is contingent to the limited capacity and duration of working memory. Another assumption refers to the concept of redundancy. It implies that information that is necessary for novices may become redundant for more advanced learners and may overload working memory. The following comments will analyze these assumptions more

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“…The questionnaire consisted of 10 statements which had to be rated on a 5-point Likert scale to the extent that they applied to the participant in the current situation. Second, motivation was measured using the Questionnaire for Current Motivation (Rheinberg et al, 2001), which was adapted to the situation of BCI training. On a 7-point Likert scale participants rated items that assessed four different components of motivation: (1) mastery confidence, which indicated how much confidence a participant had that the training would be successful, (2) fear of incompetence, which indicated how much a participant feared to fail in the training, (3) interest, which indicated how interested the participant was in the training and (4) challenge, which indicated how challenging the participant considered the training.…”

Section: Psychological Variablesmentioning

confidence: 99%

An auditory brain–computer interface (BCI)

Nijboer

Furdea

Gunst

et al. 2008

Journal of Neuroscience Methods

338

255

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Brain-computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteers participated in three training sessions consisting of 30 2-3 min runs in which they learned to increase or decrease the amplitude of sensorimotor rhythms (SMR) of the EEG. Half of the participants were presented with visual and half with auditory feedback. Mood and motivation were assessed prior to each session. Although BCI performance in the visual feedback group was superior to the auditory feedback group there was no difference in performance at the end of the third session. Participants in the auditory feedback group learned slower, but four out of eight reached an accuracy of over 70% correct in the last session comparable to the visual feedback group. Decreasing performance of some participants in the visual feedback group is related to mood and motivation. We conclude that with sufficient training time an auditory BCI may be as efficient as a visual BCI. Mood and motivation play a role in learning to use a BCI.

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FAM: Ein Fragebogen zur Erfassung aktuller Motivation in Lern- und Leistungssituationen

Cited by 290 publications

References 8 publications

The relation over time between achievement motivation and intelligence in young elementary school children: A latent cross-lagged analysis

The relation over time between achievement motivation and intelligence in young elementary school children: A latent cross-lagged analysis

Reanalyzing the expertise reversal effect

An auditory brain–computer interface (BCI)

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