Fostering retention of word learning: The number of training sessions children retrieve words positively relates to post-training retention.

During vocabulary instruction, it is important to teach words until their representations are robust enough to be retained. For adults, the number of training sessions a target item is successfully retrieved during training predicts the likelihood of post-training retention. To assess this relationship in children, we reanalyzed data from Gordon et al. (2021b, 2022). Four- to six-year-old children completed six training days with word form-object pairs and were tested one month later. Results indicate that the number of training sessions that a word form was retrieved was positively related to post-training retention. We discuss implications for vocabulary instruction and interventions.

A Word-Learning Intervention Pilot Study Utilizing Principles of Retrieval- and Criterion-Based Learning for Children With Developmental Language Disorder.

PURPOSE: Vocabulary knowledge at school entry provides an essential foundation for academic and literacy learning. Thus, school entry is an important timepoint to support word learning by children with developmental language disorder (DLD). Retrieval-based training strategies support both learning and retention of words for individuals with DLD in lab-based research. Additionally, lab-based research with adults with typical development demonstrates that pairing retrieval- and criterion-based training strategies supports learning efficiency. Currently, it is unclear if retrieval- and criterion-based training in word-learning interventions is feasible and effective for children with DLD. METHOD: In this pilot study, we taught preschool- and kindergarten-age children with DLD (N = 7) words in an intervention format. We implemented retrieval-based training in that children were asked to retrieve and produce the forms and meanings of words. We also implemented a criterion-based approach. Words were targeted until the child retrieved the form and meaning of a word at the beginning of two sessions. We assessed learning at the end of training and retention after 2- and 8-week post-training delays. RESULTS: The retrieval- and criterion-based approach was effective to support word learning for six of the seven children. Children demonstrated better learning and retention of forms than meanings. Additionally, achieving criterion with a word during training was positively related to post-training retention. CONCLUSIONS: A retrieval- and criterion-based approach is likely to support word learning during interventions for children with DLD. We include suggestions for future research to improve the effective and efficient implementation of these approaches.

A Local Planner for Accurate Positioning for a Multiple Steer-and-Drive Unit Vehicle Using Non-Linear Optimization.

This paper presents a local planning approach that is targeted for pseudo-omnidirectional vehicles: that is, vehicles that can drive sideways and rotate on the spot. This local planner-MSDU-is based on optimal control and formulates a non-linear optimization problem formulation that exploits the omni-motion capabilities of the vehicle to drive the vehicle to the goal in a smooth and efficient manner while avoiding obstacles and singularities. MSDU is designed for a real platform for mobile manipulation where one key function is the capability to drive in narrow and confined areas. The real-world evaluations show that MSDU planned paths that were smoother and more accurate than a comparable local path planner Timed Elastic Band (TEB), with a mean (translational, angular) error for MSDU of (0.0028 m, 0.0010 rad) compared to (0.0033 m, 0.0038 rad) for TEB. MSDU also generated paths that were consistently shorter than TEB, with a mean (translational, angular) distance traveled of (0.6026 m, 1.6130 rad) for MSDU compared to (0.7346 m, 3.7598 rad) for TEB.

Word Learning by Preschool-Age Children: Differences in Encoding, Re-Encoding, and Consolidation Across Learners During Slow Mapping.

PURPOSE: Children with typical development vary in how much experience they need to learn words. This could be due to differences in the amount of information encoded during periods of input, consolidated between periods of input, or both. Our primary purpose is to identify whether encoding, consolidation, or both, drive individual differences in the slow-mapping process. METHOD: Four- to 6-year-old children (N = 43) were trained on nine form-referent pairs across consecutive days. Children's ability to name referents was assessed at the beginning and end of each session. Word learning was assessed 1 month after training to determine long-term retention. RESULTS: Children with varying language knowledge and skills differed in their ability to encode words. Specifically, children varied in the number of words learned and the phonological precision of word forms at the end of the initial training session. Children demonstrated similarities in re-encoding in that they refined representations at a similar rate during subsequent sessions. Children did not differ in their ability to consolidate words between sessions, or in their ability to retain words over the 1-month delay. CONCLUSIONS: The amount of experience children need to learn words is primarily driven by the amount of information encoded during the initial experience. When provided with high-quality instruction, children demonstrate a similar ability to consolidate and retain words. Critically, word learning instruction in educational settings must include repeated explicit instruction with the same words to support learning in children with typical development and varying language skills. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.19606150.

Word Learning by Preschool-Age Children With Developmental Language Disorder: Impaired Encoding and Robust Consolidation During Slow Mapping.

Purpose Learning novel words, including the specific phonemes that make up word forms, is a struggle for many individuals with developmental language disorder (DLD). Building robust representations of words includes encoding during periods of input and consolidation between periods of input. The primary purpose of the current study is to determine differences between children with DLD and with typical development (TD) in the encoding and consolidation of word forms during the slow mapping process. Method Preschool-age children (DLD = 9, TD = 9) were trained on nine form-referent pairs across multiple consecutive training days. Children's ability to name referents at the end of training days indicated their ability to encode forms. Children's ability to name referents at the beginning of training days after a period of overnight sleep indicated their ability to consolidate forms. Word learning was assessed 1 month after training to determine long-term retention of forms. Results Throughout training, children with DLD produced fewer forms correctly and produced forms with less phonological precision than children with TD. Thus, children with DLD demonstrated impaired encoding. However, children with and without DLD demonstrated a similar ability to consolidate forms between training days and to retain forms across a 1-month delay. Conclusions Difficulties with word form learning are primarily driven by deficits in encoding for children with DLD. Clinicians and educators can support encoding by providing children with adequate exposures to target words via robust training that occurs across multiple sessions. Supplemental Material https://doi.org/10.23641/asha.16746454.

Bio-inspired homogeneous multi-scale place recognition.

Robotic mapping and localization systems typically operate at either one fixed spatial scale, or over two, combining a local metric map and a global topological map. In contrast, recent high profile discoveries in neuroscience have indicated that animals such as rodents navigate the world using multiple parallel maps, with each map encoding the world at a specific spatial scale. While a number of theoretical-only investigations have hypothesized several possible benefits of such a multi-scale mapping system, no one has comprehensively investigated the potential mapping and place recognition performance benefits for navigating robots in large real world environments, especially using more than two homogeneous map scales. In this paper we present a biologically-inspired multi-scale mapping system mimicking the rodent multi-scale map. Unlike hybrid metric-topological multi-scale robot mapping systems, this new system is homogeneous, distinguishable only by scale, like rodent neural maps. We present methods for training each network to learn and recognize places at a specific spatial scale, and techniques for combining the output from each of these parallel networks. This approach differs from traditional probabilistic robotic methods, where place recognition spatial specificity is passively driven by models of sensor uncertainty. Instead we intentionally create parallel learning systems that learn associations between sensory input and the environment at different spatial scales. We also conduct a systematic series of experiments and parameter studies that determine the effect on performance of using different neural map scaling ratios and different numbers of discrete map scales. The results demonstrate that a multi-scale approach universally improves place recognition performance and is capable of producing better than state of the art performance compared to existing robotic navigation algorithms. We analyze the results and discuss the implications with respect to several recent discoveries and theories regarding how multi-scale neural maps are learnt and used in the mammalian brain.