Michael B W Wolfe
Biographic Data
| ID | 2745786 |
|---|---|
| NAME | Michael B W Wolfe |
| GIVEN NAMES | Michael B W |
| FAMILY NAME | Wolfe |
| SIGNATURE | WOLFE M B W |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 33 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1998 |
| LATEST PUBLICATION YEAR | 2010 |
| H-INDEX | 4 |
Processing and memory of information presented in narrative or expository texts
BackgroundPrevious research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension.AimsWe expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is embedded in narrative or expository texts. We are particularly interested in how differences in the use of rele…
Learning and memory of factual content from narrative and expository text
Background. Research on the presentation of information in narrative versus expository text genres is inconclusive with respect to the question of which is more beneficial for student learning.Aims. We examine the effect of presenting factual content in either narrative or expository genres on student learning. We also consider relevant prior knowledge and working memory capacity (WMC) as potential mediating variables.Sample. Ninety university un…
Causal and Semantic Relatedness in Discourse Understanding and Representation
Processing time and memory for sentences were examined as a function of the degree of semantic and causal relatedness between sentences in short narratives. In Experiments 1-2B, semantic and causal relatedness between sentence pairs was independently manipulated. Causal relatedness was assessed through pretesting and semantic relatedness was assessed with Latent Semantic Analysis. Causal relatedness influenced processing time and memory. Semantic…
Learning from text: Matching readers and texts by latent semantic analysis
This study examines the hypothesis that the ability of a reader to learn from text depends on the match between the background knowledge of the reader and the difficulty of the text information. Latent Semantic Analysis (LSA), a statistical technique that represents the content of a document as a vector in high‐dimensional semantic space based on a large text corpus, is used to predict how much readers will learn from texts based on the estimated…
Using latent semantic analysis to assess knowledge: Some technical considerations
In another article (Wolfe et al., 1998/this issue) we showed how Latent Semantic Analysis (LSA) can be used to assess student knowledge—how essays can be graded by LSA and how LSA can match students with appropriate instructional texts. We did this by comparing an essay written by a student with one or more target instructional texts in terms of the cosine between the vector representation of the student's essay and the instructional text in ques…
Causal and Semantic Relatedness in Discourse Understanding and Representation
Processing time and memory for sentences were examined as a function of the degree of semantic and causal relatedness between sentences in short narratives. In Experiments 1-2B, semantic and causal relatedness between sentence pairs was independently manipulated. Causal relatedness was assessed through pretesting and semantic relatedness was assessed with Latent Semantic Analysis. Causal relatedness influenced processing time and memory. Semantic…
Learning from text: Matching readers and texts by latent semantic analysis
This study examines the hypothesis that the ability of a reader to learn from text depends on the match between the background knowledge of the reader and the difficulty of the text information. Latent Semantic Analysis (LSA), a statistical technique that represents the content of a document as a vector in high‐dimensional semantic space based on a large text corpus, is used to predict how much readers will learn from texts based on the estimated…
Learning and memory of factual content from narrative and expository text
Background. Research on the presentation of information in narrative versus expository text genres is inconclusive with respect to the question of which is more beneficial for student learning.Aims. We examine the effect of presenting factual content in either narrative or expository genres on student learning. We also consider relevant prior knowledge and working memory capacity (WMC) as potential mediating variables.Sample. Ninety university un…
Processing and memory of information presented in narrative or expository texts
BackgroundPrevious research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension.AimsWe expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is embedded in narrative or expository texts. We are particularly interested in how differences in the use of rele…
Using latent semantic analysis to assess knowledge: Some technical considerations
In another article (Wolfe et al., 1998/this issue) we showed how Latent Semantic Analysis (LSA) can be used to assess student knowledge—how essays can be graded by LSA and how LSA can match students with appropriate instructional texts. We did this by comparing an essay written by a student with one or more target instructional texts in terms of the cosine between the vector representation of the student's essay and the instructional text in ques…
Learning from text: Matching readers and texts by latent semantic analysis
This study examines the hypothesis that the ability of a reader to learn from text depends on the match between the background knowledge of the reader and the difficulty of the text information. Latent Semantic Analysis (LSA), a statistical technique that represents the content of a document as a vector in high‐dimensional semantic space based on a large text corpus, is used to predict how much readers will learn from texts based on the estimated…
Using latent semantic analysis to assess knowledge: Some technical considerations
In another article (Wolfe et al., 1998/this issue) we showed how Latent Semantic Analysis (LSA) can be used to assess student knowledge—how essays can be graded by LSA and how LSA can match students with appropriate instructional texts. We did this by comparing an essay written by a student with one or more target instructional texts in terms of the cosine between the vector representation of the student's essay and the instructional text in ques…
Causal and Semantic Relatedness in Discourse Understanding and Representation
Processing time and memory for sentences were examined as a function of the degree of semantic and causal relatedness between sentences in short narratives. In Experiments 1-2B, semantic and causal relatedness between sentence pairs was independently manipulated. Causal relatedness was assessed through pretesting and semantic relatedness was assessed with Latent Semantic Analysis. Causal relatedness influenced processing time and memory. Semantic…
Learning and memory of factual content from narrative and expository text
Background. Research on the presentation of information in narrative versus expository text genres is inconclusive with respect to the question of which is more beneficial for student learning.Aims. We examine the effect of presenting factual content in either narrative or expository genres on student learning. We also consider relevant prior knowledge and working memory capacity (WMC) as potential mediating variables.Sample. Ninety university un…
Processing and memory of information presented in narrative or expository texts
BackgroundPrevious research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension.AimsWe expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is embedded in narrative or expository texts. We are particularly interested in how differences in the use of rele…
Computer Science (4 works) · Linguistics (4 works) · Natural language processing (4 works) · Psychology (4 works) · Artificial Intelligence (3 works) · Cognition (3 works) · Cognitive psychology (3 works) · Latent semantic analysis (3 works) · Mathematics education (3 works) · Reading and Literacy Development (3 works)