Abstract: Techniques are described for an automated grammar teaching system that displays sentences and allows a user to identify parallel structure errors within the sentences, if any. The user may be asked to determine whether the sentences have a parallel structure error, to identify the items that should be made parallel in structure, to select items to be changed from the identified items, and to provide corrections to the selected items so that all the items form consistent parallel structures. Multiple parallel structures may be valid and accepted as correct for a given parallel structure error. To guide the user, user responses may trigger the display of remediation information, which may include reasons why the selected items are incorrect. New sentences in the teaching system may be selected based on historical data maintained for the user.

Abstract: An automated grammar teaching system displays one or more sentences and allows a user to identify a location of a run-on sentence error within a sentence. The system further allows the user to correct the identified run-on sentence error. In an embodiment, if a user incorrectly identifies a particular portion of a sentence as a run-on sentence error, then the system displays remediation information to help the user understand the portion of the sentence that the user selected. In an embodiment, if a user provides an inaccurate correction to a run-on sentence error, the system displays remediation information to explain why the correction that the user input is inaccurate. Further, the automated grammar teaching system records, as historical data, a user's actions within the system. The system uses this historical data to identify what sentences, with what kinds of run-on sentence errors, the system should provide to the user.

Abstract: Techniques are described for an automated grammar teaching system that displays sentences and allows a user to identify subject-verb agreement errors within the sentences, if any. The sentences may be presented as single sentences or as part of a paragraph. The user may be asked to determine whether the sentences are correct or incorrect, to identify the locations of verbs that should agree with a subject of the sentence, to identify the core noun that determines whether the subject is singular or plural, and to provide a new verb that agrees with the subject. To guide the user, user responses may trigger the display of remediation information, which may include identifying one or more grammar elements of the sentences that are relevant to identifying the subject-verb agreement errors. New sentences in the teaching system may be selected based on historical data maintained for the user.

Abstract: A grammar teaching system maintains and updates a mastery estimate for a grammar skill and displays an updated visual indication of this estimation. Based on user answers to grammar problems, the system updates the mastery estimate for the grammar skill. Also, a step of a grammar problem is associated with an ordered list of hints. When the user requests a hint for the problem step, the system identifies a position in the list of hints based on how many times the user has previously requested hints for the step. The system displays text that is from the hint at the identified position in the list. Further, a hint for a grammar problem step includes pointer information that refers to a portion of a sentence for the grammar problem. When the system displays the hint, the system highlights the portion of the sentence that is referred to in the pointer information.

Abstract: Techniques are described for problem selection algorithms for providing a multi-layered cognitive tutor. A repository of problems is maintained, which associates the problems with the improvement of corresponding skills according to a cognitive model. User skill levels are maintained in a user profile. Problem sets are then presented to the user in phases, where each phase may utilize different selection criteria for selecting from the repository. By varying the selection criteria between phases, for example from problems testing familiar skills to problems testing new skills, or from problems teaching few skills to problems teaching many skills, problems can be selected to address the unique requirements of each tutoring phase, from beginning to middle to end.