WO2008124465A1 - Method and system for facilitating vocabulary development - Google Patents

Abstract

The present invention is related, generally and in various embodiments, to an interactive computer-based game for improving vocabulary. One embodiment comprises a computer-based interactive word inference game in which users are presented with unknown target words in natural reading environments and asked to provide descriptive definitions or synonyms. Feedback is provided indicating how close the response is to the meaning of the target word using natural language processing tools. The feedback may comprise an output sentence containing the target word, from which an intended meaning may be inferred. Word association can thus be encouraged in an interesting and entertaining manner.

Description

METHOD AND SYSTEM FOR FACILITATING VOCABULARY DEVELOPMENT

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application Serial No. 60/910,187 filed April 4, 2007, the entire contents of which is hereby incorporated by reference herein.

BACKGROUND OF THE INVENTION FIELD OF THE INVENTION

[0002] This application discloses an invention that is related, generally and in various embodiments, to a method and system for facilitating vocabulary development. DESCRIPTION OF THE RELATED ART

[0003] Vocabulary is well recognized as an essential component of reading proficiency. For decades in reading research, it has been apparent that there exists a strong relationship between vocabulary knowledge and reading ability, with the correlation ranging between 0.6 and 0.7. (Carroll, J. B., Human Cognitive Abilities: A Survey of Factor-Analytic Studies, New York: Cambridge Press (1993)). Programs of instruction in learning word meanings by inference from written texts meet with relative success and can benefit even poor readers. Many researchers have argued that a vocabulary instructional program should be multifaceted. Four components have been identified that have empirical support for expanding students' reading vocabularies: (a) exposure to written language by engaging in wide, independent reading; (b) instruction in specific words; (c) teaching students word-learning strategies for independent vocabulary acquisition; and (d) fostering word consciousness to promote motivated, reflective word learning. [0004] Moreover, differences between written and spoken language indicate that inference from written texts may be important for vocabulary development. Written language is lexically richer than spoken language and may, therefore, provide a greater number of learning opportunities than are available in spoken context. Avid readers encounter considerably more words each year than their less well-read peers, and measures of 9 - 11 year old students' exposure to print predicts significant growth in vocabulary. Regular reading can also provide repeated opportunities to acquire, refine, and consolidate vocabulary knowledge through inference from written texts. Direct instruction in word meanings may add those items directly to an individual's vocabulary, but the ability to use those words in all of their nuances is more likely to arise from repeated exposures, through which word meanings are refined and consolidated. If word meanings are learned incrementally, a reader might require both direct instruction and exposure to that word in multiple contexts to fully fix its meaning in his or her lexicon. Indeed, such a combination of direct instruction and incidental learning appears to be the most effective method of vocabulary instruction definitions.

[0005] Accordingly, a need exists for a method and system for facilitating vocabulary development that can be a valuable supplement to direct classroom instruction by helping struggling readers acquire word learning strategies as well as provide practice for targeted vocabulary sets.

[0006] A need also exists for an easy-to-use interactive game where students can determine word meaning based on contextual cues given in text.

[0007] The disclosed embodiments are directed to solving one or more of the above problems. SUMMARY QF THE INVENTION

[0008] Before the present methods, systems and materials are described, it is to be understood that this disclosure is not limited to the particular methodologies, systems and materials described, as these may vary. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only, and is not intended to limit the scope.

[0009] It is also noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to a "text" is a reference to one or more texts and equivalents thereof known to those skilled in the art, and so forth. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. Although any methods, materials, and devices similar or equivalent to those described herein can be used in the practice or testing of embodiments, the preferred methods, materials, and devices are now described. All publications mentioned herein are incorporated by reference. Nothing herein is to be construed as an admission that the embodiments described herein are not entitled to antedate such disclosure by virtue of prior invention.

[0010] The present invention is generally directed to a computer-based interactive word inference game in which users are presented with unknown words in natural reading environments. The present invention is also directed to a method of teaching vocabulary through word association in an interesting and entertaining manner, thereby encouraging repeated play on a regular basis all of which promotes learning and better retainment. The game of the present invention supplies sentences through an automated text selection tool that finds text that are proposed to promote word learning. The users' goal is to attempt to guess the meaning of specific words based on the contextual cues given in the selected text. The game then provides feedback to the user indicating how close the users' response is to the meaning of the target word using natural language processing (NLP) tools. Statistical natural language processing uses stochastic, probabilistic and statistical methods. Statistical natural language processing also comprises all quantitative approaches to automated language processing, including probabilistic modeling, information theory, and linear algebra. The game is adapted to accommodate players of varying vocabulary skills while effectively challenging the skills of each individual player.

[0011] hi one aspect of the present invention, the method for teaching vocabulary comprises: outputting a predetermined word choice to a user on a display; electronically receiving a user's text in response to the predetermined word choice; comparing the user's text and the predetermined word choice; determining whether the user's text and the predetermined word choice are synonyms; and displaying an output sentence containing the predetermined word choice to promote word learning if the user's text and the predetermined word choice are not synonyms.

[0012] hi another aspect of the present invention, the interactive computer-based game for teaching vocabulary comprises: a display for displaying a predetermined word choice to a user; a computer-readable medium for electronically receiving a user's text; a processor for comparing the user's text and the predetermined word choice, wherein the predetermined word choice is stored on the computer-readable medium; and wherein the processor analyzes the predetermined word choice and determines an output sentence containing the predetermined word choice to display to the user to promote word learning. [0013] While a simple definition task may be as beneficial as the game of the present invention, the results of various studies indicate users find the game more interactive and engaging due to its interactive nature. Since users have the freedom to generate meaning in their own words, the task of word learning is more easily consolidated in memory. Indeed, recall has been shown to facilitate memory and possible learning of word meanings.

[0014] Other methods and computer-based games for teaching vocabulary may also be performed within the scope of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Aspects, features, benefits and advantages of the embodiments described herein will be apparent with regard to the following description, appended claims and accompanying drawings where:

[0016] FIG. 1 illustrates sample dialogue in accordance with the game of the present invention; and

[0017] FIG. 2 illustrates a block diagram of exemplary hardware that may be used to contain and/or implement the program instructions of a system embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0018] It is to be understood that at least some of the figures and descriptions of the invention have been simplified to focus on elements that are relevant for a clear understanding of the invention, while eliminating, for purposes of clarity, other elements that those of ordinary skill in the art will appreciate may also comprise a portion of the invention. However, because such elements are well known in the art, and because they do not necessarily facilitate a better understanding of the invention, a description of such elements is not provided herein. [0019] The present invention is generally directed to a computer-based interactive word inference game in which users are presented with unknown words in natural reading environments. The game of the present invention supplies sentences through an automated text selection tool that finds text that are proposed to promote word learning. The users' goal is to attempt to guess the meaning of specific words based on the contextual cues given in the short selected text. The game then provides feedback to the user indicating how close the users' response is to the meaning of the target word using natural language process tools.

[0020] The game may be implemented in software, hardware, or firmware, and may comprise a portion of a computing device. According to various embodiments, the game may be implemented as a software application, a computer program, etc., utilizing any suitable computer language (e.g., C, C++, Delphi, Java, JavaScript, Perl, Visual Basic, VBScript, etc.) and may be embodied permanently or temporarily in any type of machine, component, physical or virtual equipment, storage medium, or propagated signal capable of delivering instructions to a device. The software code may be stored as a series of instructions or commands on a computer-readable medium such that when a processor reads the medium, the functions described herein are performed.

[0021] As used herein, the term "computer-readable medium" may include, for example, magnetic and optical memory devices such as diskettes, compact discs of both readonly and writeable varieties, optical disk drives, and hard disk drives. A computer-readable medium may also include memory storage that can be physical, virtual, permanent, temporary, semi-permanent and/or semi-temporary. A computer-readable medium may further include one or more propagated signals, and such propagated signals may or may not be transmitted on one or more carrier waves. One skilled in the art will appreciate that the functionality of the game of the present invention may be distributed across any number of modules. According to various embodiments, such modules may be installed on separate, distinct systems. Also, different functional aspects of such modules may be installed on separate, distinct devices.

[0022] hi an embodiment of the present invention, the game operates on three main parameters: (1) text identification; (2) natural language understanding; and (3) pedagogy for instruction. First, for text identification, contextual informativeness is defined as the extent to which a text provides useful cues that could support appropriate inferences about word meaning. Contextual informativeness is an estimation of the learnability of a word given a set of contexts or sentences over a corpus. Sentences were abstracted from Source Finder® and Lexile®, two large corpora based on narrative and expository text.

[0023] In an embodiment of the present invention, a word in a sentence is displayed to a user and the user is asked to type in his knowledge of the word. Users are allowed to input any response they think will convey the meaning of the word (e.g., definition, synonym, word in a new sentence).

[0024] FIG. 1 illustrates an embodiment of the game of the present invention, hi the sample dialogue of FIG. 1, a user must try to infer or guess what "precipice" means 10 given the context of the sentence offered. In this embodiment, prompt box 15 prompts the user to describe the word. The guess is entered into a response box as shown in step 20 and natural language processing tools evaluate the correctness of the user's response. Each single response for a target word is given a score of either 0, 1, or 2. After each response, the user receives a new sentence containing the target word 30, as well as feedback regarding on his guess. The user must obtain four points to "pass" a word and move on to a new word 60. If the user does not obtain four points in a total of six guesses, the user misses the word and is automatically moved on the next word. After the user passes or missed the target word, the definition is displayed. The prompts to the user can be a variety of different phrases requesting information from the user as shown in steps 35 and 45.

[0025] hi an embodiment of the present invention, the game utilizes two methods for natural language processing. The first method is a synonym word list that has been predefined for each target word used in the study. This synonym word list database is bootstrapped with a corpus defined vector database that makes approximations of word relationships. This algorithm was adopted to balance recall and precision for users' guesses. Responses are first evaluated against the synonym word list of the respective target word for a two-point reward. If the response cannot be found in the synonym word list, the response is compared in the vector approach. Responses above the threshold for vector evaluations receive one-point.

[0026] FIG. 2 depicts a block diagram of exemplary hardware that may be used to contain and/or implement the program instructions of a system embodiment. Referring to FIG. 2, a bus 128 serves as the main information highway interconnecting the other illustrated components of the hardware. CPU 102 is the central processing unit of the system, performing calculations and logic operations required to execute a program. Read only memory (ROM) 118 and random access memory (RAM) 120 constitute exemplary memory devices.

[0027] A disk controller 104 interfaces with one or more optional disk drives to the system bus 128. These disk drives may be external or internal floppy disk drives such as 110, CD ROM drives 106, or external or internal hard drives 108. As indicated previously, these various disk drives and disk controllers are optional devices. [0028] Program instructions may be stored in the ROM 118 and/or the RAM 120. Optionally, program instructions may be stored on a computer readable medium such as a floppy disk or a digital disk or other recording medium, a communications signal or a carrier wave.

[0029] An optional display interface 122 may permit information from the bus 128 to be displayed on the display 124 in audio, graphic or alphanumeric format. Communication with external devices may optionally occur using various communication ports 126. An exemplary communication port 126 may be attached to a communications network, such as the Internet or an intranet.

[0030] In addition to the standard computer-type components, the hardware may also include an interface 112 which allows for receipt of data from input devices such as a keyboard 114 or other input device 116 such as a remote control, pointer and/or joystick.

[0031] An embedded system may optionally be used to perform one, some or all of the described operations. Likewise, a multiprocessor system may optionally be used to perform one, some or all of the described operations. Example 1: Development of Game Based on Study of a Sample of Students

Method

[0032] Sample: 163 students in grades six through eight were used in the study.

[0033] Procedure: Students were randomly assigned to one of three word-list conditions in accordance with the present invention. Each condition instructed on ten different target words for roughly thirty minutes. Use of the tool was self paced but users were encouraged to try to finish all ten target words in the allotted time frame.

[0034] Measures: Pre and post free recall measures were used to evaluate learning gains from the tool. Participants were instructed to write down anything that they thought the word could mean. Pre and post measures included all the words used in the game (i.e., ten experimental words) plus ten control words from one of the other two word-list conditions. In total there were twenty words in the free recall task. Each word was scored on a three-point scale (0, 1, 2) by the scoring algorithm. Therefore the highest score that could be given on the pre or post test was 40.

[0035] Additionally, a series of usability preference questions were administered (4- point scale; 1 = strongly disagree, 4 = strongly agree) to investigate how participants liked the game.

Analysis and Results

[0036] Two primarily analyses were conducted in this study. First, learning gains were evaluated through a repeated measures comparison between pre and post-tests crossed with various individual differences. Second, a series of usability questions were posed to investigate what the users thought about the game. Finally, the natural language processing performance in the game was evaluated.

[0037] Significant gains were found overall between pre-test (Mean = 0.10, Standard Deviation = 0.10) and post-test (M = 0.20, SD = 0.15), p < 0.001, d = .78. There was no significant interaction between control and experimental words in the pre-test and post-test, which suggested that the pretest was not affecting word learning, p < 0.005. Additionally, the relationship between points received in the game and pre-post test differences were investigated. Points received were split into three groups (low, medium, and high) and an interaction was found by points received in the game and pre and post differences, p < 0.05. Table 1 below displays the means and standard deviations for the six groups. T-tests revealed significant differences between point groups (low pre-test - low post-test, medium pre-test- medium post- test, high pre-test - high post-test) between pre and post, p < 0.001.

Table 1 : Pre and post mean proportions by points received in game.

[0038] As can be seen, users who received more points in the game displayed greater effect sizes between pre and post-test (low: d = 0.68; medium: d = 0.93; high: d = 1.03). This suggests that successful performance in the game leads to greater learning gains between the pretest and post-test.

[0039] Other factors like the time spent on the task, word list conditions, and usability preferences had no significant relations to pre or post learning gains.

[0040] A three-choice recognition test was also administered after the post-test to measure partial knowledge not detected in the free recall task (M = 0.43, SD = 0.31). It is difficult to compare this performance to the free recall pretest, but it does shed light on other learning that could be taking place from the game.

[0041] Table 2 displays the results of the usability questionnaire. Users appeared to moderately enjoy using the game. Table 2

Conclusion

[0042] The results of this study show promise regarding the development of a vocabulary instruction game. While the differences between the pre and post-tests are modest, if students would have had more time using the game, more substantial gains would be found. Since this study was run in conjunction with another study, users only had around twenty-five minutes to interact with the game.

[0043] Using synonym word lists as answer keys provided more precision to user response evaluation, but at the cost of reducing the array of possible correct answers for a particular target word. Taking a combined approach that employs natural language processing tools and a synonym word list keys appears to be a good option for future research studies.

[0044] While a simple definition task may be as beneficial as the game of the present invention, the results of the usability task indicate students may find the game more interactive and engaging due to its interactive nature. Since users have the freedom to generate meaning in their own words, the task of word learning is more easily consolidated in memory. Indeed, recall has been shown to facilitate memory and possible learning of word meanings.

[0045] It will be appreciated that various of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. It will also be appreciated that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those of ordinary skill in the art which are also intended to be encompassed by the disclosed embodiments.

Claims

WHAT IS CLAIMED IS:

1. A method for teaching vocabulary, the method comprising: outputting a target word to a user on a display; electronically receiving a user's text in response to the target word; comparing the user's text and the target word; determining whether the user's text and the target word are synonyms; and displaying an output sentence containing the target word to promote word learning if the user's text and the target word are not synonyms.

2. The method of claim 1, wherein comparing the user's text and the target word comprises using natural language processing.

3. The method of claim 2, wherein natural language processing comprises utilizing a synonym word list to compare to the user's text.

4. The method of claim 3, wherein the synonym word list is predefined for each target word and stored on the computer-readable medium.

5. The method of claim 3, further comprising determining how close the user's text is to the target word using a corpus-defined vector database that approximates word relationships.

6. The method of claim 1, wherein the output sentence is supplied through an automated text selection tool.

7. The method of claim 1, wherein the user's text is the user's estimation as to the predetermined word choice's meaning.

8. The method of claim 7, further comprising assigning points based on the user's text.

9. An interactive computer-based game for teaching vocabulary, the game comprising: a display for displaying a target word to a user; a computer- readable medium for electronically receiving a user's text; and a processor for comparing the user's text and the target word, wherein the target word is stored on the computer-readable medium, wherein the processor analyzes the target word and determines an output sentence containing the target word to display to the user to promote word learning if the user's text and the target word are not synonyms.

10. The computer-based game of claim 9, wherein the processor analyzes the target word using natural language processing.

11. The computer-based game of claim 10, wherein natural language processing comprises utilizing a synonym word list to compare to the user's text.

12. The computer-based game of claim 11, wherein the synonym word list is predefined for each target word and stored on the computer-readable medium.

13. The computer-based game of claim 11, further comprising determining how close the user's text is to the target word using a corpus-defined vector database that approximates word relationships.

14. The computer-based game of claim 9, wherein the output sentence is supplied through an automated text selection tool.

15. The computer-based game of claim 9, wherein the user's text is the user's estimation as to the target word's meaning.

16. The computer-based game of claim 15, wherein the processor assigns points based on the user's text.