1. A learning analysis system for analyzing student performance and learning activity in a learning environment, the system comprising: a monitor; an electronic computer processor in communication with the monitor, wherein the processor is programmed to execute the function of an inference engine, wherein the inference engine is programmed to receive at least the following input data based on interaction, by students, with a computer-based learning environment that comprises at least one access device, wherein the input data comprises clickstream data received via the at least one access device, and the inference engine is programmed to calculate: (a) student-learning data based on the clickstream data, wherein the student learning data is associated with the students performing at least one activity in the learning environment, and (b) knowledge component model data based on the clickstream data, wherein the knowledge component model data comprises a mapping of at least one knowledge component to the at least one activity to be performed by the students in the learning environment; wherein the inference engine is further programmed to generate, in response to the student learning data and the knowledge component model data, at least one of a statistical probability distribution or a point estimate for at least the following components of a statistical model: (a) a learning state parameter representing a level of learning each of the students has attained for at least one knowledge component, wherein the at least one knowledge component comprises a predetermined number of skills, facts, concepts, strategies, or relationships regarding subject matter within a learning domain and is specific to an individual student, (b) a skill dynamics parameter representing a relationship between practice and the learning state parameter for the at least one knowledge component, wherein the skill dynamics parameter is specific to an individual knowledge component, and (c) a variability parameter representing variability in the learning state parameter and the skill dynamics parameter across the students; wherein the electronic computer processor is programmed to provide a screen display on the monitor that displays a plurality of learning objectives, wherein at least one of the plurality of learning objectives provides an interactive link in the screen display that, when activated by a user, causes the monitor to display a graphical representation of a student learning and performance metric based on the statistical model; and wherein the graphical representation of the at least one student learning and performance metric comprises information illustrating at least one of which knowledge component of a plurality of knowledge components were not well learned across the students, which students achieved comparatively lower levels of learning for a given learning objective, or which learning objective had not been practiced sufficiently.
1. A learning analysis system for analyzing student performance and learning activity in a learning environment, the system comprising: a monitor; an electronic computer processor in communication with the monitor, wherein the processor is programmed to execute the function of an inference engine, wherein the inference engine is programmed to receive at least the following input data based on interaction, by students, with a computer-based learning environment that comprises at least one access device, wherein the input data comprises clickstream data received via the at least one access device, and the inference engine is programmed to calculate: (a) student-learning data based on the clickstream data, wherein the student learning data is associated with the students performing at least one activity in the learning environment, and (b) knowledge component model data based on the clickstream data, wherein the knowledge component model data comprises a mapping of at least one knowledge component to the at least one activity to be performed by the students in the learning environment; wherein the inference engine is further programmed to generate, in response to the student learning data and the knowledge component model data, at least one of a statistical probability distribution or a point estimate for at least the following components of a statistical model: (a) a learning state parameter representing a level of learning each of the students has attained for at least one knowledge component, wherein the at least one knowledge component comprises a predetermined number of skills, facts, concepts, strategies, or relationships regarding subject matter within a learning domain and is specific to an individual student, (b) a skill dynamics parameter representing a relationship between practice and the learning state parameter for the at least one knowledge component, wherein the skill dynamics parameter is specific to an individual knowledge component, and (c) a variability parameter representing variability in the learning state parameter and the skill dynamics parameter across the students; wherein the electronic computer processor is programmed to provide a screen display on the monitor that displays a plurality of learning objectives, wherein at least one of the plurality of learning objectives provides an interactive link in the screen display that, when activated by a user, causes the monitor to display a graphical representation of a student learning and performance metric based on the statistical model; and wherein the graphical representation of the at least one student learning and performance metric comprises information illustrating at least one of which knowledge component of a plurality of knowledge components were not well learned across the students, which students achieved comparatively lower levels of learning for a given learning objective, or which learning objective had not been practiced sufficiently. 22. The system of claim 1 , wherein the graphical representation of the at least one student learning and performance comprises information illustrating at least one of which knowledge component of a plurality of knowledge components were not well learned across the students, which students achieved comparatively lower levels of learning for a given learning objective, or which learning objective had not been practiced sufficiently.