scholarly journals Assessing Low-level Cognitive Processes of Word Recognition

2020 ◽  
Vol 9 (2) ◽  
pp. 55-62
Author(s):  
Michael Holsworth ◽  
Keyword(s):  
Reading Comprehension ◽  
Word Recognition ◽  
Cognitive Processing ◽  
Semantic Knowledge ◽  
Orthographic Knowledge ◽  
Cognitive Resources ◽  
Low Level ◽  
Phonological Knowledge ◽  
Recognition Ability ◽  
High Level

A fundamental skill required for vocabulary development is word recognition ability. According to Perfetti (1985), word recognition ability relies on low-level cognitive processing skill to be automatic and efficient in order for cognitive resources to be allocated to high-level processes such as inferencing and schemata activation needed for reading comprehension. The low-level processes include orthographic knowledge, semantic knowledge, and phonological awareness. These low-level processes must be efficient, fluent, and automatic in second language readers in order for them to achieve the ultimate goal of reading comprehension. This article briefly describes the concept of word recognition, its relation to vocabulary, and three tests that were designed to measure the three components of word recognition (orthographic, semantic, and phonological knowledge) in a longitudinal study that investigated the effects of word recognition training on reading comprehension.

scholarly journals The Use of Orthographic Knowledge in Beginning Reading

1986 ◽  
Vol 18 (3) ◽  
pp. 229-241 ◽  
Author(s):  
Lauren Leslie ◽  
Brenda Thimke
Keyword(s):  
Word Recognition ◽  
Recognition Test ◽  
Second Graders ◽  
Beginning Reading ◽  
Orthographic Knowledge ◽  
Search Tasks ◽  
Recognition Ability ◽  
Word Search ◽  
The Relationship

The purpose of the present study was to determine the relationship between word recognition ability, knowledge of orthographic structures, and use of orthographic knowledge in word recognition. Fifty-six first and second graders were administered a word recognition test, two tests of orthographic knowledge, and two search tasks. The results indicated that when searching for multiple word targets children with word recognition levels of less than 2–2 searched similarly through all fields, whereas children with word recognition levels of 2–2+ searched faster through pseudowords and nonwords than through words. When searching for members of a category, children with word recognition levels below 2–1 searched faster through nonwords and pseudowords than through words providing no evidence for the use of orthography in word search. Children with word recognition levels above 2–1 searched faster through nonwords than through pseudowords and words, demonstrating a generalized effect of orthographic structure.

A 3D Engineering Model Retrieval Algorithm Based on Relevance Feedback and Features Combination

2013 ◽  
Vol 579-580 ◽  
pp. 340-344
Author(s):  
Ting Zhuang ◽  
Xu Tang Zhang ◽  
Zhen Xiu Hou
Keyword(s):  
Relevance Feedback ◽  
3D Model ◽  
3D Models ◽  
Semantic Knowledge ◽  
Retrieval Algorithm ◽  
Engineering Model ◽  
Feedback Information ◽  
Low Level ◽  
Model Retrieval ◽  
High Level

In order to reuse 3D models and design knowledge efficiently, a number of 3D model retrieval algorithms based on content features of models have been proposed in recent years. Although, the features-based methods have achieved some progress, there are two limitations stilly. The first, single content feature cant be suit for all kinds of 3D models; different features have different strengths and weakness. The second, semantic gap, the semantic of model is independent from low-level characteristics. For those two issues, we present a 3D engineering model retrieval algorithm based on relevance feedback and features combination in this paper. The proposed method takes advantage of multiple features by allying them with weights. In the retrieval process, our method utilizes the Particle Swarm Optimization to update the weights dynamically based on users relevance feedback information in order to narrowing the gap between high-level semantic knowledge and low-level content features. The Experiments, based on publicly available 3D model database Engineering Shape Benchmark (ESB) developed by Purdue University, suggested that the proposed approach has better retrieval ability than traditional ones.

scholarly journals THE INFLUENCE OF THINK-ALOUD STRATEGY AND READING INTEREST TOWARD READING COMPREHENSION STUDENTS OF ADAB FACULTY IAIN RADEN FATAH PALEMBANG

2018 ◽  
Vol 16 (1) ◽  
pp. 66-83
Author(s):  
Nyayu Yayu Suryani
Keyword(s):  
Reading Comprehension ◽  
Random Sampling ◽  
Think Aloud ◽  
Low Level ◽  
High Interest ◽  
High Level ◽  
Reading Interest

Penelitian ini bertujuan untuk mengetahui apakah: (1) ada perbedaan yang signifikan dalam pemahaman membaca dengan menggunakan strategi think-aloud dan strategi konvensional; (2) ada perbedaan yang signifikan dalam pemahaman membaca antara strategi think-aloud dan teknik konvensional berdasarkan tingkat high level dalam minat membaca; (3) ada perbedaan yang signifikan dalam pemahaman membaca antara strategi think-aloud dengan menggunakan teknik konvensional berdasarkan tingkat low level dalam minat membaca; (4) ada pengaruh interaksi dari strategi yang digunakan dan minat baca yang diajarkan terhadap prestasi pemahaman membaca. Populasi penelitian adalah mahasiswa semester dua Fakultas Adab di IAIN Raden Fatah Palembang yang terdiri dari 248 siswa. Sampel penelitian ini adalah 84 mahasiswa dengan menggunakan random sampling. Metode penelitian ini adalah metode eksperimental. Penelitian ini dikategorikan dalam (low and high interest). Penelitian ini dapat disimpulkan bahwa: (1) terdapat perbedaan yang signifikan dalam pencapaian pemahaman membaca antara strategi Think-aloud dan strategi konvensional. (2) ada perbedaan yang signifikan dalam pencapaian pemahaman membaca antara strategi think-aloud dengan menggunakan teknik konvensional berdasarkan high interest dalam minat membaca. (3) ada perbedaan yang signifikan dalam pencapaian pemahaman membaca antara strategi think-aloud dengan menggunakan teknik konvensional berdasarkan low interest minat membaca. (4) ada pengaruh interaksi yang signifikan antara strategi think-aloud dan minat membaca terhadap pemahaman membaca.

scholarly journals Recognition of Orthographic Structure during Beginning Reading

1981 ◽  
Vol 13 (4) ◽  
pp. 313-324 ◽  
Author(s):  
Lauren Leslie ◽  
Albert J. Shannon
Keyword(s):  
Word Recognition ◽  
Discriminant Function Analysis ◽  
Grade Level ◽  
Function Analysis ◽  
Letter Recognition ◽  
Orthographic Knowledge ◽  
Second Grade ◽  
The Third ◽  
Chance Performance ◽  
Recognition Ability

The development of knowledge of orthographic structure among beginning readers was examined by testing their ability to discern which word in a pair looked most like a word. One hundred forty-five children in preschool, kindergarten, first and second grades were given three tasks measuring knowledge of orthographic structure and tests of letter, numeral and word recognition on two occasions six months apart. One orthographic task assessed the knowledge that words did not contain numbers; another assessed knowledge that certain consonant clusters do not occur in English. Results showed that word-recognition ability, rather than grade level, correlated highly (.80) with orthographic knowledge. Letter recognition correlated (.66) with knowledge that words do not contain numbers. The results of a discriminant-function analysis indicated an early second-grade level of word recognition predicted above-chance performance on the third orthographic task. The results were discussed in relation to an interactive-compensatory model of reading.

scholarly journals Voxelwise encoding models show that cerebellar language representations are highly conceptual

2021 ◽  
Author(s):  
Amanda LeBel ◽  
Shailee Jain ◽  
Alexander G. Huth
Keyword(s):  
Natural Language ◽  
Recent Work ◽  
Cognitive Processing ◽  
Language Processing ◽  
Motor Planning ◽  
Model Framework ◽  
Low Level ◽  
Semantic Categories ◽  
Feature Spaces ◽  
High Level

AbstractThere is a growing body of research demonstrating that the cerebellum is involved in language understanding. Early theories assumed that the cerebellum is involved in low-level language processing. However, those theories are at odds with recent work demonstrating cerebellar activation during cognitive tasks. Using natural language stimuli and an encoding model framework, we performed an fMRI experiment where subjects passively listened to five hours of natural language stimuli which allowed us to analyze language processing in the cerebellum with higher precision than previous work. We used this data to fit voxelwise encoding models with five different feature spaces that span the hierarchy of language processing from acoustic input to high-level conceptual processing. Examining the prediction performance of these models on separate BOLD data shows that cerebellar responses to language are almost entirely explained by high-level conceptual language features rather than low-level acoustic or phonemic features. Additionally, we found that the cerebellum has a higher proportion of voxels that represent social semantic categories, which include “social” and “people” words, and lower representations of all other semantic categories, including “mental”, “concrete”, and “place” words, than cortex. This suggests that the cerebellum is representing language at a conceptual level with a preference for social information.Significance StatementRecent work has demonstrated that, beyond its typical role in motor planning, the cerebellum is implicated in a wide variety of tasks including language. However, little is known about the language representations in the cerebellum, or how those representations compare to cortex. Using voxelwise encoding models and natural language fMRI data, we demonstrate here that language representations are significantly different in the cerebellum as compared to cortex. Cerebellum language representations are almost entirely semantic, and the cerebellum contains over-representation of social semantic information as compared to cortex. These results suggest that the cerebellum is not involved in language processing per se, but cognitive processing more generally.

scholarly journals A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles

2020 ◽  
Vol 6 (8) ◽  
pp. 78
Author(s):  
Dario Cazzato ◽  
Claudio Cimarelli ◽  
Jose Luis Sanchez-Lopez ◽  
Holger Voos ◽  
Marco Leo
Keyword(s):  
Object Detection ◽  
Unmanned Aerial Vehicles ◽  
Semantic Knowledge ◽  
Low Level ◽  
Multiple Sensors ◽  
Aerial Vehicles ◽  
Trade Offs ◽  
Methodological Approaches ◽  
High Level ◽  
Technological Constraints

The spread of Unmanned Aerial Vehicles (UAVs) in the last decade revolutionized many applications fields. Most investigated research topics focus on increasing autonomy during operational campaigns, environmental monitoring, surveillance, maps, and labeling. To achieve such complex goals, a high-level module is exploited to build semantic knowledge leveraging the outputs of the low-level module that takes data acquired from multiple sensors and extracts information concerning what is sensed. All in all, the detection of the objects is undoubtedly the most important low-level task, and the most employed sensors to accomplish it are by far RGB cameras due to costs, dimensions, and the wide literature on RGB-based object detection. This survey presents recent advancements in 2D object detection for the case of UAVs, focusing on the differences, strategies, and trade-offs between the generic problem of object detection, and the adaptation of such solutions for operations of the UAV. Moreover, a new taxonomy that considers different heights intervals and driven by the methodological approaches introduced by the works in the state of the art instead of hardware, physical and/or technological constraints is proposed.

scholarly journals Actual and Perceived Questions Asked by Preceptors with and Without the Use of Bug-in-Ear Technology

2018 ◽  
Vol 13 (2) ◽  
pp. 102-111
Author(s):  
Sara L. Nottingham
Keyword(s):  
Athletic Training ◽  
Cognitive Processing ◽  
Clinical Reasoning ◽  
Clinical Education ◽  
Instructional Strategy ◽  
Question Type ◽  
Student Interactions ◽  
Low Level ◽  
Classification Framework ◽  
High Level

Context: Questioning is an instructional strategy used by preceptors to assess knowledge and improve clinical reasoning in students. Preceptors face challenges asking high-level questions, and bug-in-ear (BIE) technology may be one way to address these challenges. Objective: Assess the cognitive level of questions asked by preceptors with and without the use of BIE technology. Design: Mixed methods. Setting: Seven clinical education sites affiliated with 3 Commission on Accreditation of Athletic Training Education–accredited undergraduate athletic training programs. Patients or Other Participants: A total of 13 athletic training students and 8 preceptors. Main Outcome Measure(s): Preceptor-student interactions were observed and audio recorded for 2 days without and 2 days with the availability of BIE technology. Cognitive levels of questions were analyzed using the Question Classification Framework and a 2 (Intervention) × 3 (Question Type) analysis of variance. Interviews were conducted to obtain participants' experiences with and perceptions of questioning and BIE technology. Interviews were analyzed by 2 individuals using an inductive coding process. Trustworthiness was established with member-checking, multiple-analyst triangulation, and data-source triangulation. Results: Preceptors asked 1044 questions, including 46.94% low-level (n = 557), 2.38% high-level (n = 24), and 50.69% other (n = 463), such as yes/no questions, during 149 hours of observation. Preceptors asked more questions during the control sessions than when they used BIE technology (39.1 ± 31.7 versus 26.1 ± 20.4 questions; F1,7 = 6.3; P = .04), although participants perceived the opposite. Two themes emerged from the interview data: (1) Preceptors use questioning to develop clinical reasoning in students, and (2) BIE technology facilitates low-level questioning. Conclusions: Although preceptors primarily asked low-level and basic recall questions of their students during clinical education, participants described the use of strategic sequencing of questions to facilitate clinical reasoning. Preceptors should be encouraged to ask more high-level questions and sequence them to target higher cognitive processing. Bug-in-ear technology was not effective at facilitating effective questioning in clinical education.

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