In most rule-learning experiments subjects (Ss) are trained with both positive and negative instances of the rule. However, in most traditional artificial grammar learning (AGL) experiments Ss are trained with positive instances only and using very complex rules. In a typical training phase Ss are unaware of the underlying rules governing the stimuli, and are instead instructed to do an irrelevant task. After training they are told about the rules, and then have to differentiate between positive and negative stimuli. Ss’ typical performance is significantly better than chance, although Ss are unable to verbalise the rules and think they are guessing. This dissociation of performance and verbalisation led Reber (e.g. 1967) to conclude that S...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) performance reflects both implicit and explicit processes and has ...
Actively searching for the rules of an artificial grammar has often been shown to produce no more kn...
A current theoretical debate regards whether rule-based or similarity based learning prevails during...
Artificial grammar learning (AGL) experiments are used to investigate the possibility that separate ...
Two experiments examined the claim for distinct implicit and explicit learning modes in the artifici...
Evidence for unconscious learning has typically been based on dissociations between direct and indir...
Although there is variability in nonnative grammar learning outcomes, the contributions of training ...
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In ge...
In everyday life, there is considerable need for rule learning. Behavioral and human brain imaging s...
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In ge...
Although there is variability in nonnative grammar learning outcomes, the contributions of training ...
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In ge...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) performance reflects both implicit and explicit processes and has ...
Actively searching for the rules of an artificial grammar has often been shown to produce no more kn...
A current theoretical debate regards whether rule-based or similarity based learning prevails during...
Artificial grammar learning (AGL) experiments are used to investigate the possibility that separate ...
Two experiments examined the claim for distinct implicit and explicit learning modes in the artifici...
Evidence for unconscious learning has typically been based on dissociations between direct and indir...
Although there is variability in nonnative grammar learning outcomes, the contributions of training ...
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In ge...
In everyday life, there is considerable need for rule learning. Behavioral and human brain imaging s...
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In ge...
Although there is variability in nonnative grammar learning outcomes, the contributions of training ...
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In ge...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...
Artificial grammar learning (AGL) has become an important tool used to understand aspects of human l...