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Central issues. For both experimental and modeling field it is important to start from theory A common theory (and a common lexicon ) will help building the interface between modelers and experimentalist Features mean different things for different people!
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Central issues • For both experimental and modeling field it is important to start from theory • A common theory (and a common lexicon) will help building the interface between modelers and experimentalist • Features mean different things for different people! • Make your research question as precise as possible • Important step taken in this workshop!
Central issues • Experimentalists • Need more data, more experiments (to test theories) • Modelers • Need better models which can predict future data • Ideally, models make predictions, which can be tested experimentally, leading to improved models…
Central issues • Theory of language acquisition • Bottom-up: often aimed for in speech research • Hard to determine relevant features, categories, etc. • Often unsuccessful: lacking insight into which data/features are important for the language learner • Top-down: example Petra Hendriks and colleagues • Many assumption regarding relevant features, categories, etc. • Or both? • Integration of information from various domains (Feldman) • Is ‘good enough’ sufficient?
Central issues • Input • Too rich/not rich enough? • How much input is needed? • How are the relevant cues in the input selected by the learner? • What filters/constraints does the language learner use?
Bold claims about early language acquisition Kuhl et al. (2008)
Recurrent issues • Experiments • Only trust experimental results that are replicable! • As a community we are responsible for replicating studies and informing the field about non-replicable results • More communication within the field
Recurrent issues • Models need to be built on reliable experimental results/claims • Communication between modelers and experimentalists is essential • Models need to make sure that experimentalists know what good models are • Communication between modelers and experimentalists is essential
Central issues • Development • How can it be described? • What triggers development? • Longitudinal (perception) studies are rare
Recurrent issues • Experiments • Do the dependent measures (often looking time) reflect underlying knowledge and processes sufficiently? • Are time course measures more insightful? • Discrimination is not categorization! • Selection of stimulus materials is crucial • Sufficiently informed by linguistic theory? • Comparison of stimuli materials in similar paradigms to gain insight into which cues in the materials help/hinder learning
Recurrent issues • Models need to be cognitively plausible • Different types of models: • Models are not just fancy calculators (although they can be), • but preferably also make predictions and provide insight into mechanisms of acquisition • Models give insight into development • Of individual children? • Or language learners in general? • Urgent need to compare models! • Do modelers of acquisition of syntax encounter the same issues as those modeling early speech perception?
Other issues • Cross-linguistic studies (non-Indoeuropean) • Variation • In input • Between learners (individual differences) • Learning in the lab vs. learning in real life • Feedback • Role of social interaction • Abstraction/Generalization • Relation perception/production?
Share data and • For language resources and technology infrastructure !
