Strategi meminimalkan beban kognitif eksternal dalam pembelajaran matematika berdasarkan load cognitive theory

Memahami objek, konsep, prosedur merupakan salah satu tujuan mempelajari pelajaran matematika disekolah. Muatan materi yang cendrung kompleks dengan elemen-elemen yang abstrak menjadi masalah bagi siswa sehingga memunculkan beban kognitif, diantaranya adalah beban kognitif eksternal. Tujuan dari penelitian ini untuk menunjukkan beberapa strategi yang perlu diperhatikan dalam mendesain pembelajaran matematika agar dapat meminimalkan beban kognitif eksternal. Penelitian ini berupa studi kepustakaan (library research). Teknik pengumpulan data dalam penelitian ini, dilakukan dengan melakukan penelusuran referensi secara online melalui beberapa sumber basis data Google Cendikia, ERIC Institute of Education Science, serta Science Direct. Analisis data dalam penelitian ini menggunakan metode analisis isi (content analysis). Hasil kajian dalam studi ini terdapat 8 strategi dalam mendesain pembelajaran matematika untuk meminimalkan beban kognitif eksternal diantaranya The Goal-Free Effect, The Worked Exampel Effect, The Split-Attention Effect, The Modality Effect, The Redundancy Effect, The Element Interactivity Effect, The Imagination Effect dan The Guidance Fading Effect.Understanding objects, concepts, procedures is one of the goals of studying mathematics in school. Material content that tends to be complex with abstract elements becomes a problem for students so that it creates cognitive loads, including external cognitive loads. The purpose of this study is to show several strategies that need to be considered in designing mathematics learning in order to minimize external cognitive load. This research is in the form of library research (library research). The data collection technique in this study was carried out by searching for references online through several Google Cendikia database sources, ERIC Institute of Education Science, and Science Direct. Analysis of the data in this study using content analysis method. The results of the study in this study there are 8 strategies in designing mathematics learning to minimize external cognitive load including The Goal-Free Effect, The Worked Exampel Effect, The Split-Attention Effect, The Modality Effect, The Redundancy Effect, The Element Interactivity Effect, The Imagination Effect and The Guidance Fading Effect.

Representing uncertainty in the Rescorla-Wagner model: Blocking, the redundancy effect, and outcome base rate

It is generally assumed that the Rescorla and Wagner (1972) model adequately accommodates the full results of simple cue competition experiments in humans (e.g. Dickinson et al., 1984), while the Bush and Mosteller (1951) model cannot. We present simulations that demonstrate this assumption is wrong in at least some circumstances. The Rescorla-Wagner model, as usually applied, fits the full results of a simple forward cue-competition experiment no better than the Bush-Mosteller model. Additionally, we present a novel finding, where letting the associative strength of all cues start at an intermediate value (rather than zero), allows this modified model to provide a better account of the experimental data than the (equivalently modified) Bush-Mosteller model. This modification also allows the Rescorla-Wagner model to account for a redundancy effect experiment (Uengoer et al., 2013); something that the unmodified model is not able to do. Furthermore, the modified Rescorla-Wagner model can accommodate the effect of varying the proportion of trials on which the outcome occurs (i.e. the base rate) on the redundancy effect (Jones et al., 2019). Interestingly, the initial associative strength of cues varies in line with the outcome base rate. We propose that this modification provides a simple way of mathematically representing uncertainty about the causal status of novel cues within the confines of the Rescorla-Wagner model. The theoretical implications of this modification are discussed. We also briefly introduce free and open resources to support formal modelling in associative learning. Keywords: associative learning, prediction error, uncertainty, modelling, blocking, redundancy effect, open science.

Representing uncertainty in the Rescorla-Wagner model: blocking, the redundancy effect, and outcome base rate

It is generally assumed that the Rescorla and Wagner (1972) model adequately accommodates the full results of simple cue competition experiments in humans (e.g. Dickinson et al., 1984), while the Bush and Mosteller (1951) model cannot. We present simulations that demonstrate this assumption is wrong in at least some circumstances. The Rescorla-Wagner model, as usually applied, fits the full results of a simple forward cue-competition experiment no better than the Bush-Mosteller model. Additionally, we present a novel finding, where letting the associative strength of all cues start at an intermediate value (rather than zero), allows this modified model to provide a better account of the experimental data than the (equivalently modified) Bush-Mosteller model. This modification also allows the Rescorla-Wagner model to account for a redundancy effect experiment (Uengoer et al., 2013); something that the unmodified model is not able to do. Furthermore, the modified Rescorla-Wagner model can accommodate the effect of varying the proportion of trials on which the outcome occurs (i.e. the base rate) on the redundancy effect (Jones et al., 2019). Interestingly, the initial associative strength of cues varies in line with the outcome base rate. We propose that this modification provides a simple way of mathematically representing uncertainty about the causal status of novel cues within the confines of the Rescorla-Wagner model. The theoretical implications of this modification are discussed. We also briefly introduce free and open resources to support formal modelling in associative learning.

The Redundancy Effect on Human Predictive Learning: Evidence against a Propositional Interpretation

The redundancy effect is the finding of greater learning when an X stimulus is trained in an A+ AX+ blocking procedure, than when a Y stimulus is trained in a BY+ CY- discrimination procedure. These findings are new and theoretically challenging for all conditioning theories that calculate learning based on a common error. For this reason, we alternatively examined the possibility that the phenomenon is the result of a propositional reasoning. In an experiment, we replicated the basic effect and we found out that the addition of instructions on the occurrence of the consequences at a submaximal level does not have a significant impact on the redundancy effect. These findings are discussed with regard to a propositional and associative approach based on the assumption that the experimental stimuli share a common feature.

The redundancy effect is related to a lack of conditioned inhibition: Evidence from a task in which excitation and inhibition are symmetrical

Rescorla and Wagner’s model of learning describes excitation and inhibition as symmetrical opposites. However, tasks used in human causal learning experiments, such as the allergist task, generally involve learning about cues leading to the presence or absence of the outcome, which may not reflect this assumption. This is important when considering learning effects which provide a challenge to this model, such as the redundancy effect. The redundancy effect describes higher causal ratings for the blocked cue X than for the uncorrelated cue Y in the design A+/AX+/BY+/CY–, the opposite pattern to that predicted by the Rescorla–Wagner model, which predicts higher associative strength for Y than for X. Crucially, this prediction depends on cue C gaining some inhibitory associative strength. In this article, we used a task in which cues could have independent inhibitory effects on the outcome, to investigate whether a lack of inhibition was related to the redundancy effect. In Experiment 1, inhibition for C was not detected in the allergist task, supporting this possibility. Three further experiments using the alternative task showed that a lack of inhibition was related to the redundancy effect: the redundancy effect was smaller when C was rated as inhibitory. Individual variation in the strength of inhibition for C also determined the size of the redundancy effect. Given that weak inhibition was detected in the alternative scenario but not in the allergist task, we recommend carefully choosing the type of task used to investigate associative learning phenomena, as it may influence results.