1. Field of the Invention
The present invention relates generally to literacy tutoring and, more specifically, to automated, computer-based reading tutoring systems and methods particularly adapted to provide literacy tutoring in conjunction with user-specific content learning.
2. Brief Description of the Related Art
The demand for alternatives to traditional classroom instruction has been steadily growing, with increasing numbers of individuals being interested in self-guided learning experiences for personal fulfillment and/or career development. Concomitantly, many institutions are recognizing the need to implement educational and training opportunities to retain motivated employees and to remain competitive. Various institutions, for example, are being called upon to provide options for independent study using distance learning technologies. Presently available computer-based education or training, while responding to the aforementioned demands, has presented numerous drawbacks. Many computer-based training systems and methods (CBT) have proven to be too simplistic and “lock-step” to be of much value beyond the acquisition of rudimentary skills or information. Intelligent tutoring systems and methods (ITS) have proven valuable in some highly constrained domains, but generally require levels of effort and expense that are impractical for most applications.
In the area of literacy, there is a great need for self-guided reading tutoring systems and methods to improve the reading skills of learners of various ages. Many learners, particularly adults, are more comfortable and motivated to learn when in a private setting without the fear of public scrutiny and embarrassment. Self-guided reading tutoring systems and methods allow students to learn in comfort and privacy as well as to set their own time and pace for learning, which might otherwise not be possible in a traditional classroom setting.
Non-automated reading tutorials utilizing a hierarchical series of reading passages arranged according to levels of difficulty have been proposed. The passages typically derive from multiple sources and relate to a single topic. A student is assigned the least difficult passage to read, and an instructor thereafter manually evaluates the student's understanding of the passage. Where adequate comprehension is demonstrated, the student advances to the next level of difficulty, and the instructor must repeat the process of manually evaluating the student's reading comprehension at each level and selecting the next reading passage. Where the student fails to pass a particular level, the procedure is repeated for as many passages as needed at the same level until the student passes. Since reading tutoring systems and methods of the aforementioned type are very labor intensive, standardized generic instructional materials are developed and used with all students regardless of a student's interests, work experience, work requirements, prior knowledge of the subject matter, and individual learning differences. Unless a student happens to be interested in the subject matter, has frequent and timely interactions with an instructor, and is able to progress quickly and easily through the levels of difficulty, whatever motivation the student initially brings to the task is soon dissipated. Furthermore, traditional reading tutorials of this type are usually lacking in specific features by which vocabulary and reading fluency skills can be effectively enhanced.
An example of a self-paced, “CBT-like” educational package including a reading tutorial is the PLATO ® educational package developed by TRO Learning, Inc. The PLATO ® reading series is less labor intensive than traditional manual reading tutorials, but does not incorporate artificial intelligence to provide customized, learner-specific guidance and motivation. As with traditional manual reading tutorials, the PLATO ® reading series is pre-packaged with generic content.
There is significant agreement among educators and researchers that a student's ability to produce a good summary of lesson text is superior to other forms of assessment in evaluating the student's reading comprehension and that learning to write good summaries of lesson text is an effective way to develop reading comprehension strategies and skills. A major drawback to using student summaries for instruction and assessment of reading comprehension, however, is the time and effort required for human experts to evaluate the summaries and provide timely feedback to the student. Since written summaries must be scored by a human instructor, a significant delay in time ensues before the results of the scoring can be used to enable instruction to proceed. Accordingly, it is more typical for reading comprehension to be assessed using objective questions that can be scored automatically, but which are less valid in measuring actual comprehension.
A major impediment to providing automated, computer-based reading tutoring systems and methods is the difficulty involved in automating the critical functions of an expert human tutor to achieve an “ITS-like” learning experience with a “CBT-like” expenditure of effort and expense. In particular, the inability to automate the analysis and structuring of textual instructional material within a very large domain of discourse, the evaluation of a student's current reading level, the determination of the student's understanding of the instructional material, and the generation of recommendations about the next level of reading difficulty appropriate for the student are great deterrents to the implementation of automated, computer-based reading tutorials. While latent semantic analysis (LSA), a fully automatic mathematical/statistical technique for extracting and inferring relations of expected contextual usage of words in passages of discourse, has been found capable of simulating a variety of human cognitive phenomena, its applicability to automated, computer-based reading tutoring systems and methods has thus far not been recognized. U.S. Pat. No. 5,987,446 to Corey et al., U.S. Pat. No. 5,839,106 to Bellegarda, U.S. Pat. No. 5,301,019 to Landauer et al., and U.S. Pat. No. 4,839,853 to Deerwester et al. are representative of prior applications for latent semantic techniques.
Reading accuracy and fluency are known to play an important role in developing reading comprehension. Oral reading fluency is important because, without developing sufficient speed to maintain important sentence structures in short term memory, comprehension fails due to insufficiency of memory resources. Therefore, developing sufficient speed and fluency in reading are critical to improving reading comprehension. While speed in reading is greatly improved by repetition and practice, most learners are likely to avoid practice opportunities that might arise in traditional classroom settings due to the fear of failure. One-on-one fluency tutoring can be conducted with less fear of embarrassment, but is cost-prohibitive and impractical for most learners. Traditional reading tutorials, which typically are lacking in fluency instruction, thusly fail to address the needs of learners for whom the speed and accuracy with which they read are obstacles to improved reading comprehension. In particular, it is not possible with traditional reading tutorials to practice oral reading fluency in an automated environment using speech recognition software.