Papers by Virginia Clinton
Journal of Research in Reading, Jun 7, 2012
Mathematics curricula are frequently rich with visuals, but these visuals are often not designed ... more Mathematics curricula are frequently rich with visuals, but these visuals are often not designed for optimal use of students’ limited cognitive resources. The authors of this study revised the visuals in a mathematics lesson based on instructional design principles. The purpose of this study is to examine the effects of these revised visuals on students’ cognitive load, cognitive processing, learning, and interest. Middle-school students (N = 62) read a lesson on early algebra with original or revised visuals while their eye movements were recorded. Students in the low prior knowledge group had less cognitive load and cognitive processing with the revised lesson than the original lesson. However, the reverse was true for students in the middle prior knowledge group. There were no effects of the revisions on learning. The findings are discussed in the context of the expertise reversal effect as well as the cognitive theory of multimedia learning and cognitive load theory.
Learning from visual representations is enhanced when learners appropriately integrate correspond... more Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly assigned to learn about probabilistic reasoning from one of 4 computer-based lessons generated from a 2 (color coding/no color coding) by 2 (labeling/no labeling) between-subjects design. Learners added the labels or color coding at their own pace by clicking buttons in a computer-based lesson. Participants’ eye movements were recorded while viewing the lesson. Labeling was beneficial for learning, but color coding was not. In addition, labeling, but not color coding, increased attention to important information in the table and time with the lesson. Both labeling and color coding increased looks between the text and corresponding information in the table. The findings provide support for the multimedia principle (Mayer, 2009), and they suggest that providing labeling enhances learning about probabilistic reasoning from text and tables.
Solving mathematics story problems requires text comprehension skills. However, previous studies ... more Solving mathematics story problems requires text comprehension skills. However, previous studies have
found few connections between traditional measures of text readability and performance on story
problems. We hypothesized that recently developed measures of readability and topic incidence measured
by text-mining tools may illuminate associations between text difficulty and problem-solving
measures. We used data from 3,216 middle and high school students from 10 schools using the Cognitive
Tutor Algebra program; these schools were geographically, socioeconomically, racially, and ethnically
diverse. We found that several indicators of the readability and topic of story problems were associated
with students’ tendency to give correct answers and request hints in Cognitive Tutor. We further
examined the individual skill of writing an algebraic expression from a story scenario, and examined
students at the lowest performing schools in the sample only, and found additional associations for these
subsets. Key readability and topic categories that were related to problem-solving measures included
word difficulty, text length, pronoun use, sentence similarity, and topic familiarity. These findings are
discussed in the context of models of mathematics story problem solving and previous research on text
comprehension.
Keywords: readability, algebra, data-mining, intelligent tutoring system, topic interest
Journal of Research in Reading, 2012
Topic interest and learning from texts have been found to be positively associated with each othe... more Topic interest and learning from texts have been found to be positively associated with each other. However, the reason for this positive association is not well understood. The purpose of this study is to examine a cognitive process, inference generation, that could explain the positive association between interest and learning from texts. In Study 1, sixty undergraduate students participated by reading two science texts, which differed in coherence levels, silently. The results replicated previous findings that topic interest is positively associated with recall and accurate answers to comprehension questions for both texts. In Study 2, sixty-nine undergraduate students participated by reading the same two science texts while thinking aloud. The results indicated that topic interest was positively associated with inference generation while reading for the more coherently-written text. Subsequent analyses indicated inference generation partly explained the positive association between topic interest and accurate answers to comprehension questions for the more coherently-written text. The findings from Study 2 were independent of the effects of reading comprehension skill. Theoretical implications of the findings, in regard to standards of coherence and depth of processing while reading, are discussed.
Journal of Experimental Education
To learn from a text, students must make meaningful connections among related ideas in that text.... more To learn from a text, students must make meaningful connections among related ideas in that text. This study examined the effectiveness of two methods of improving connections— elaborative interrogation and diagrams—in written lessons about posterior probability. Undergraduate students (N = 198) read a lesson in one of three questioning conditions (read twice, embedded questioning, and elaborative interrogation) and one of three diagram conditions (text only, diagram without redundant text, and diagram with redundant text). Elaborative interrogation negatively affected learning from the lesson, relative to reading the lesson twice. One possible explanation for this finding is that the quality of answers to the elaborative interrogations was poor. When the lesson was read twice, diagrams helped learning from the lesson relative to text only. Implications of these findings for instruction in probabilistic reasoning are discussed.
Solving mathematics story problems requires text comprehension skills. However, previous studies ... more Solving mathematics story problems requires text comprehension skills. However, previous studies have found few connections between traditional measures of text readability and performance on story problems. We hypothesized that recently developed measures of readability and topic incidence measured by text-mining tools may illuminate associations between text difficulty and problem-solving measures. We used data from 3,216 middle and high school students from 10 schools using the Cognitive Tutor Algebra program; these schools were geographically, socioeconomically, racially, and ethnically diverse. We found that several indicators of the readability and topic of story problems were associated with students’ tendency to give correct answers and request hints in Cognitive Tutor. We further examined the individual skill of writing an algebraic expression from a story scenario, and examined students at the lowest performing schools in the sample only, and found additional associations for these subsets. Key readability and topic categories that were related to problem-solving measures included word difficulty, text length, pronoun use, sentence similarity, and topic familiarity. These findings are discussed in the context of models of mathematics story problem solving and previous research on text comprehension
Words can be informative linguistic markers of psychological constructs. The purpose of this stu... more Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students (N = 218) reading narrative texts were hand-coded for inferences. These data were also processed with a computer text analysis tool, Linguistic Inquiry and Word Count (LIWC), for percentages of word use in the following categories: cognitive mechanism words, nonfluencies, and 9 types of function words. Findings indicate that cognitive mechanisms were an independent, positive predictor of connections to background knowledge (i.e., elaborative inference generation) and nonfluencies were an independent, negative predictor of connections within the text (i.e., bridging inference generation). Function words did not provide unique variance towards predicting inference generation. These findings are discussed in the context of a cognitive reflection model and the differences between bridging and elaborative inference generation. In addition, potential practical implications for intelligent tutoring systems and computer-based methods of inference identification are presented.
Topic interest and learning from texts have been found to be positively associated with each othe... more Topic interest and learning from texts have been found to be positively associated with each other. However, the reason for this positive association is not well understood. The purpose of this study is to examine a cognitive process, inference generation, that could explain the positive association between interest and learning from texts. In Study 1, sixty undergraduate students participated by reading two science texts, which differed in coherence levels, silently. The results replicated previous findings that topic interest is positively associated with recall and accurate answers to comprehension questions for both texts. In Study 2, sixty-nine undergraduate students participated by reading the same two science texts while thinking aloud. The results indicated that topic interest was positively associated with inference generation while reading for the more coherently-written text. Subsequent analyses indicated inference generation partly explained the positive association between topic interest and accurate answers to comprehension questions for the more coherently-written text. The findings from Study 2 were independent of the effects of reading comprehension skill. Theoretical implications of the findings, in regard to standards of coherence and depth of processing while reading, are discussed.
Instructional Science, Sep 2014
Student approaches to learning have been a popular area of research in educational psychology. On... more Student approaches to learning have been a popular area of research in educational psychology. One useful framework for understanding student approaches to learning is through Biggs’ presage–process–product model. The purpose of this study is to examine the process stage of the 3P model. Undergraduate students (N = 67) thought aloud while reading two science texts, then wrote recalls and answered comprehension questions. As hypothesized, a deep approach to learning was positively associated with making connections, examining the logic in the text, and accurate answers to the comprehension questions. Mediation analyses indicated that behavior during the process of learning explained the positive association between a deep approach to learning and accurate answers to the comprehension questions. No hypotheses regarding a surface approach to learning were supported. The findings from this study support the characterization that students with a deep approach to learning engage meaningfully with their course material. These findings are discussed in the context of the 3P model.
Journal of Research in Reading, Nov 2014
The purpose of this study was to determine if there are gender differences among elementary schoo... more The purpose of this study was to determine if there are gender differences among elementary school-aged students in regard to the inferences they generate during reading. Fourth-grade students (130 females; 126 males) completed think-aloud tasks while reading one practice and one experimental narrative text. Females generated a larger number and a greater proportion of reinstatement inferences than did males (Cohen’s d = .34, p = .01; Cohen’s d = .26, p = .04, respectively). In contrast, there was no evidence for gender differences in other types of think-aloud responses. These findings suggest that males and females differ in their use of cognitive processes that underlie reading comprehension, particularly with respect to the likelihood of retrieval of information from episodic memory.
Reading Psychology, 2015
The purpose of this study was to examine the associations between reading motivation and inferenc... more The purpose of this study was to examine the associations between reading motivation and inference generation while reading. Undergraduate participants (N = 69) read two science articles while thinking aloud, completed a standardized reading comprehension assessment, and self reported their habitual reading motivation. Findings indicate that overall reading motivation, one component of intrinsic motivation (reading as a sense of self) and one component of extrinsic motivation (reading to do well in other realms) were positively associated with text-connecting inference generation independent of reading comprehension skill. These findings are discussed in the context of standards of coherence.
Proceedings by Virginia Clinton
Non-Cognitive Factors & Personalization for Adaptive Learning Workshop at the 7th International Conference of Educational Data Mining, 2014
Intelligent tutoring systems (ITSs) that personalize
instruction to individual learner backgrou... more Intelligent tutoring systems (ITSs) that personalize
instruction to individual learner background and
preferences have emerged in K-16 classroom settings all
over the world. In mathematics instruction, ITSs may be
especially important for tracking mathematical skill
development over time. However, recent research has
pointed to the importance of text-based measures when
solving mathematics word problems, suggesting that in
order to accurately model the student it is important to
understand how they respond to text characteristics. We
investigate the impact of text-based factors (readability and
problem topic) on the solving of mathematics story
problems using a corpus of N = 3394 students working
through an ITS for algebra, Cognitive Tutor Algebra. We
leverage recent advances in computerized text-mining to
automate fine-grained text analyses of many different word
problems. We find that several elements of the text of
mathematics word problems matter for performance –
including the concreteness of the problem’s topic, the
length and conciseness of the story’s text, and the words
and phrases used.
Proceedings of the 35th annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, 2013
Solving mathematics story problems requires text comprehension skills. However, previous studies ... more Solving mathematics story problems requires text comprehension skills. However, previous studies have found few connections between traditional measures of readability and performance on story problems. We hypothesized that recently-developed measures of readability may illuminate associations between text difficulty and problem solving. We used data from 3,394 middle and high school students solving algebra story problems in Cognitive Tutor Algebra. We found that several indicators of readability were negatively associated with incorrect answers. Moreover, indicators of readability were associated with students requesting hints from Cognitive Tutor. These findings are discussed in the context of models of algebra problem solving and previous research on text difficulty in solving story problems.
Research findings on integrating visuals with text have indicated that students learn less when i... more Research findings on integrating visuals with text have indicated that students learn less when interesting but irrelevant materials, such as decorative images, are included (e.g., Harp & Mayer, 1998; Mayer, 2009; Sweller, 2005). The basic idea is that these can overload processing and disrupt student learning and performance, but evidence with math problems is mixed (e.g., Berends & van Lieshout, 2009). Based on the theories and previous research findings, we revised eight problems in an existing mathematics curriculum. We used four types of revisions within-subjects; three removed decorative images and one added relevant information to the visual.
Fifty seventh-grade students each completed eight problems. We assessed students’ problem solving accuracy and strategies in addition to their math background, math attitudes, and contextual recall as these measures potentially influence the effect of visual representations. Revising the problems in concordance with the research-based principles did not have a consistent effect on performance or strategy use, nor were these effects related to students' math ability or anxiety. This is in contrast to what is often found in applications of these principles in science (see Mayer, 2009). Adding labeled dimensions to a visual increased the use of units, although not necessarily in a correct way. Of note, we found that the revisions did not affect students' opinions about the problems. The recall measures indicated that students encoded the contextual information from the text and/or visuals. Additional processing of the contextual information (as seen by correct recall) tended to be associated with lower mathematical accuracy, but this was unrelated to the presence of the decorative image. Overall, the lack of consistent effects indicates the need for further research on the influence of these principles in mathematics.
Given the multitude of visual representations in mathematics textbooks, it is critical to understand how visual information (both decorative and relevant) influences students' problem solving. The math ability level of our students was relatively high, and other individual differences may explain the lack of consistent effects. Investigating student attitudes as well as their contextual memory broadens the research base, so that researchers and educators can develop more nuanced understanding of the uses of visuals. Most clear from this research, however, is the need to further address how to enhance the integration of visual and verbal information in the mathematical problem solving of K – 12 students.
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Papers by Virginia Clinton
found few connections between traditional measures of text readability and performance on story
problems. We hypothesized that recently developed measures of readability and topic incidence measured
by text-mining tools may illuminate associations between text difficulty and problem-solving
measures. We used data from 3,216 middle and high school students from 10 schools using the Cognitive
Tutor Algebra program; these schools were geographically, socioeconomically, racially, and ethnically
diverse. We found that several indicators of the readability and topic of story problems were associated
with students’ tendency to give correct answers and request hints in Cognitive Tutor. We further
examined the individual skill of writing an algebraic expression from a story scenario, and examined
students at the lowest performing schools in the sample only, and found additional associations for these
subsets. Key readability and topic categories that were related to problem-solving measures included
word difficulty, text length, pronoun use, sentence similarity, and topic familiarity. These findings are
discussed in the context of models of mathematics story problem solving and previous research on text
comprehension.
Keywords: readability, algebra, data-mining, intelligent tutoring system, topic interest
Proceedings by Virginia Clinton
instruction to individual learner background and
preferences have emerged in K-16 classroom settings all
over the world. In mathematics instruction, ITSs may be
especially important for tracking mathematical skill
development over time. However, recent research has
pointed to the importance of text-based measures when
solving mathematics word problems, suggesting that in
order to accurately model the student it is important to
understand how they respond to text characteristics. We
investigate the impact of text-based factors (readability and
problem topic) on the solving of mathematics story
problems using a corpus of N = 3394 students working
through an ITS for algebra, Cognitive Tutor Algebra. We
leverage recent advances in computerized text-mining to
automate fine-grained text analyses of many different word
problems. We find that several elements of the text of
mathematics word problems matter for performance –
including the concreteness of the problem’s topic, the
length and conciseness of the story’s text, and the words
and phrases used.
Fifty seventh-grade students each completed eight problems. We assessed students’ problem solving accuracy and strategies in addition to their math background, math attitudes, and contextual recall as these measures potentially influence the effect of visual representations. Revising the problems in concordance with the research-based principles did not have a consistent effect on performance or strategy use, nor were these effects related to students' math ability or anxiety. This is in contrast to what is often found in applications of these principles in science (see Mayer, 2009). Adding labeled dimensions to a visual increased the use of units, although not necessarily in a correct way. Of note, we found that the revisions did not affect students' opinions about the problems. The recall measures indicated that students encoded the contextual information from the text and/or visuals. Additional processing of the contextual information (as seen by correct recall) tended to be associated with lower mathematical accuracy, but this was unrelated to the presence of the decorative image. Overall, the lack of consistent effects indicates the need for further research on the influence of these principles in mathematics.
Given the multitude of visual representations in mathematics textbooks, it is critical to understand how visual information (both decorative and relevant) influences students' problem solving. The math ability level of our students was relatively high, and other individual differences may explain the lack of consistent effects. Investigating student attitudes as well as their contextual memory broadens the research base, so that researchers and educators can develop more nuanced understanding of the uses of visuals. Most clear from this research, however, is the need to further address how to enhance the integration of visual and verbal information in the mathematical problem solving of K – 12 students.
found few connections between traditional measures of text readability and performance on story
problems. We hypothesized that recently developed measures of readability and topic incidence measured
by text-mining tools may illuminate associations between text difficulty and problem-solving
measures. We used data from 3,216 middle and high school students from 10 schools using the Cognitive
Tutor Algebra program; these schools were geographically, socioeconomically, racially, and ethnically
diverse. We found that several indicators of the readability and topic of story problems were associated
with students’ tendency to give correct answers and request hints in Cognitive Tutor. We further
examined the individual skill of writing an algebraic expression from a story scenario, and examined
students at the lowest performing schools in the sample only, and found additional associations for these
subsets. Key readability and topic categories that were related to problem-solving measures included
word difficulty, text length, pronoun use, sentence similarity, and topic familiarity. These findings are
discussed in the context of models of mathematics story problem solving and previous research on text
comprehension.
Keywords: readability, algebra, data-mining, intelligent tutoring system, topic interest
instruction to individual learner background and
preferences have emerged in K-16 classroom settings all
over the world. In mathematics instruction, ITSs may be
especially important for tracking mathematical skill
development over time. However, recent research has
pointed to the importance of text-based measures when
solving mathematics word problems, suggesting that in
order to accurately model the student it is important to
understand how they respond to text characteristics. We
investigate the impact of text-based factors (readability and
problem topic) on the solving of mathematics story
problems using a corpus of N = 3394 students working
through an ITS for algebra, Cognitive Tutor Algebra. We
leverage recent advances in computerized text-mining to
automate fine-grained text analyses of many different word
problems. We find that several elements of the text of
mathematics word problems matter for performance –
including the concreteness of the problem’s topic, the
length and conciseness of the story’s text, and the words
and phrases used.
Fifty seventh-grade students each completed eight problems. We assessed students’ problem solving accuracy and strategies in addition to their math background, math attitudes, and contextual recall as these measures potentially influence the effect of visual representations. Revising the problems in concordance with the research-based principles did not have a consistent effect on performance or strategy use, nor were these effects related to students' math ability or anxiety. This is in contrast to what is often found in applications of these principles in science (see Mayer, 2009). Adding labeled dimensions to a visual increased the use of units, although not necessarily in a correct way. Of note, we found that the revisions did not affect students' opinions about the problems. The recall measures indicated that students encoded the contextual information from the text and/or visuals. Additional processing of the contextual information (as seen by correct recall) tended to be associated with lower mathematical accuracy, but this was unrelated to the presence of the decorative image. Overall, the lack of consistent effects indicates the need for further research on the influence of these principles in mathematics.
Given the multitude of visual representations in mathematics textbooks, it is critical to understand how visual information (both decorative and relevant) influences students' problem solving. The math ability level of our students was relatively high, and other individual differences may explain the lack of consistent effects. Investigating student attitudes as well as their contextual memory broadens the research base, so that researchers and educators can develop more nuanced understanding of the uses of visuals. Most clear from this research, however, is the need to further address how to enhance the integration of visual and verbal information in the mathematical problem solving of K – 12 students.
The purpose of our study is to understand why diagrams increase learning from lessons. To address this issue, we randomly assigned undergraduates (N = 36) to read a probability lesson either with or without diagrams, while their eye movements were recorded. Students whose lessons included diagrams solved more probability problems correctly at post-test than did students whose lessons did not include diagrams. Students whose lessons included diagrams also had smaller average pupil size and spent less time reading the text than did students whose lessons did not include diagrams. Pupil size and reading times typically increase with task difficulty (Rayner, 1997; van Gog et al., 2009); therefore, this finding indicates that the diagrams lessened the difficulty of reading the lesson. In addition, students whose lessons included diagrams frequently looked to and from the diagram and the text. Their looks to and from the diagram and text may indicate that they were integrating the visual and verbal representations in the lesson (Mason, Tornatora, & Pluchino, 2012).
These findings indicate that both of the previously proposed reasons may explain why students whose lessons included diagrams answered more problems correctly than did students whose lessons did not have diagrams. One is that the diagrams made the lesson text easier to understand; therefore, students could focus their efforts on extracting the content of the lesson, rather than working to comprehend the text. The other is that diagrams encourage students to make connections within the lesson material, which prompts deeper comprehension. These findings enrich our understanding of the benefits of visual representations.
There is empirical evidence that decorative images have a negative influence on learning (Levin, Anglin, & Carney, 1987), likely because of the seductive details effect. In contrast, contextual images have been shown to help with aspects of reading comprehension for some populations (cf. Pike, Barnes, & Barron, 2010), although the effects of contextual images on learning from math lessons have not been explored. It is unknown whether contextual images would distract from mathematics learning or if they would benefit mathematics learning through assistance with reading comprehension. The purpose of this study is to examine the influence of contextual and decorative images on learning from a mathematics lesson. Eye-tracking methodology was used to determine if the inclusion of these images, which are mathematically irrelevant, caused diminished visual attention to the lesson text and graphs, which are mathematically relevant.
Forty-one undergraduate students participated by reading four mathematics lessons on functions. The data indicated that there was little visual attention to either decorative or contextual images. Including decorative or contextual images did not influence visual attention towards math relevant information in the lesson (i.e., the graph and lesson text). Therefore, it can be inferred that the students tended to ignore the images in the lessons. There were no differences in written recalls of lessons or answers to questions across image conditions. Compared to the lesson text, little visual attention was directed towards the graphs, which were mathematically relevant visual representations. This is unfortunate because graphs can assist in mathematics learning (Shah, Mayer, & Hegarty, 1999). An important direction for future research may be to develop methods to direct learner attention towards graphs.