total time a student took to solve a given exercise.

-   `lecture_complete`: Whether a student completes studying a video lecture offered to him/her.

-   `review_correctness` : Whether a student responds correctly to a previously solved exercise.

In the aforementioned example, features like `response_correctness` and `timeliness` directly evaluates the educational values of a student’s interaction, while it is somewhat debatable whether `platform` and `longest_answer` are also capable of addressing such quality. Accordingly, we define the concept of assessment and assessment modeling as the following.

\[def:am\] An *assessment* $a_{t}^{k}$ of the $t$’th interaction $I_t$ is a feature of $I_t$ which can act as a criterion for pedagogical evaluation. The collection $A_{t} = \{a_{t}^{1}, \dots, a_{t}^{m}\}$ of assessments is a subset of the available features $\{f_{i}^{1}, \dots, f_{i}^{n}\}$ of $I_t$. An *assessment modeling* is the prediction of assessment $a_{t}^{k}$ for some $k$ from the interactions $[I_1, \dots, I_{t-1}, I_t, I_{t+1}, \dots, I_T]$. That is, the prediction of $$\label{eq:am}
p(a_{t}^{k} | I_1, \dots, I_{t-1}, I_t \setminus \Gamma(a_{t}^{k}), I_{t+1}, \dots, I_T).$$

\[ex:am\] Among the interactive features listed in Example \[ex:kt\], we consider the `response_correctness`, `timeliness`, `course_dropout`, `elapsed_time`, `lecture_complete` and `review_correctness` as assessments. For example, `response_correctness` is the primary assessment as whether a student responded correctly 