Towards a quantitative evaluation of the relationship between the domain knowledge and the ability to assess peer work

In this work we present the preliminary results provided by the statistical modeling of the cognitive relationship between the knowledge about a topic a the ability to assess peer achievements on the same topic. Our starting point is Bloom's taxonomy of educational objectives in the cognitive domain, and our outcomes confirm the hypothesized ranking. A further consideration that can be derived is that meta-cognitive abilities (e.g., assessment) require deeper domain knowledge

Modeling peer assessment as a personalized predictor of teacher's grades: The case of OpenAnswer

Questions with open answers are rarely used as e-learning assessment tools because of the resulting high workload for the teacher/tutor that should grade them. This can be mitigated by having students grade each other's answers, but the uncertainty on the quality of the resulting grades could be high. In our OpenAnswer system we have modeled peer-assessment as a Bayesian network connecting a set of sub-networks (each representing a participating student) to the corresponding answers of her graded peers. The model has shown good ability to predict (without further info from the teacher) the exact teacher mark and a very good ability to predict it within 1 mark from the right one (ground truth). From the available datasets we noticed that different teachers sometimes disagree in their assessment of the same answer. For this reason in this paper we explore how the model can be tailored to the specific teacher to improve its prediction ability. To this aim, we parametrically define the CPTs (Conditional Probability Tables) describing the probabilistic dependence of a Bayesian variable from others in the modeled network, and we optimize the parameters generating the CPTs to obtain the smallest average difference between the predicted grades and the teacher's marks (ground truth). The optimization is carried out separately with respect to each teacher available in our datasets, or respect to the whole datasets. The paper discusses the results and shows that the prediction performance of our model, when optimized separately for each teacher, improves against the case in which our model is globally optimized respect to the whole dataset, which in turn improves against the predictions of the raw peer-assessment. The improved prediction would allow us to use OpenAnswer, without teacher intervention, as a class monitoring and diagnostic tool

Supporting mediated peer-evaluation to grade answers to open-ended questions

We show an approach to semi-automatic grading of answers given by students to open ended questions (open answers). We use both peer-evaluation and teacher evaluation. A learner is modeled by her Knowledge and her assessments quality (Judgment). The data generated by the peer- and teacher- evaluations, and by the learner models is represented by a Bayesian Network, in which the grades of the answers, and the elements of the learner models, are variables, with values in a probability distribution. The initial state of the network is determined by the peer-assessment data. Then, each teacher’s grading of an answer triggers evidence propagation in the network. The framework is implemented in a web-based system. We present also an experimental activity, set to verify the effectiveness of the approach, in terms of correctness of system grading, amount of required teacher's work, and correlation of system outputs with teacher’s grades and student’s final exam grade

Improved computation of individual ZPD in a distance learning system

This paper builds upon theoretical studies in the field of social constructivism. Lev Vygotsky is considered one of the greatest representatives of this research line, with his theory of the Zone of Proximal Development (ZPD). Our work aims at integrating this concept in the practice of a computer-assisted learning system. For each learner, the system stores a model summarizing the current Student Knowledge (SK). Each educational activity is specified through the deployed content, the skills required to tackle it, and those acquired, and is further annotated by the effort estimated for the task. The latter may change from one student to another, given the already achieved competence. A suitable weighting of the robustness (certainty) of student’s skills, stored in SK, and their combination are used to verify the inclusion of a learning activity in the student’s ZPD. With respect to our previous work, the algorithm for the calculation of the ZPD of the individual student has been optimized, by enhancing the certainty weighting policy, and a graphical display of the ZPD has been added. Thanks to the latter, the student can get a clear vision of the learning paths that he/she can presently tackle. This both facilitates the educational process, and helps developing the metacognitive ability self-assessment

Layered map reasoning

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Non-zinc mediated inhibition of carbonic anhydrases: coumarins are a new class of suicide inhibitors.

The X-ray crystal structure of the adduct between the zinc metalloenzyme carbonic anhydrase II (CA, EC 4.2.1.1) with the recently discovered natural product coumarin derivative 6-(1S-hydroxy-3-methylbutyl)-7-methoxy-2H-chromen-2-one showed the coumarin hydrolysis product, a cis-2-hydroxy-cinnamic acid derivative, and not the parent coumarin, bound within the enzyme active site. The bound inhibitor exhibits an extended, two-arm conformation that effectively plugs the entrance to the enzyme active site with no interactions with the catalytically crucial zinc ion. The inhibitor is sandwiched between Phe131, with which it makes an edge-to-face stacking, and Asn67/Glu238sym, with which it makes several polar and hydrogen bonding interactions. This unusual binding mode, with no interactions between the inhibitor molecule and the active site metal ion is previously unobserved for this enzyme class and presents a new opportunity for future drug design campaigns to target a mode of inhibition that differs substantially from classical inhibitors such as the clinically used sulfonamides and sulfamates. Several structurally simple coumarin scaffolds were also shown to inhibit all 13 catalytically active mammalian CA isoforms, with inhibition constants ranging from nanomolar to millimolar. The inhibition is time dependent, with maximum inhibition being observed after 6 h.No Full Tex

OpenAnswer, a framework to support teacher's management of open answers through peer assessment

Open-ended questions are an important means to support analysis and assessment of students; they can be of extraordinary effectiveness for the assessment of higher cognitive levels of the Bloom's Taxonomy. On the other hand, assessing open answers (textual, freely shaped, answers to a question) is a hard task. In this paper we describe an approach to open answers evaluation based on the use of peer-assessment: in a social-collaborative e-learning setting implemented by the OpenAnswer web system, the students answer questions and rate others' (and may be own) answers, while the teacher marks a subset of the answers so to allow the system inferring the rest of the marks. The aim of our system is to ease the teacher's marking burden and allow for a more extensive use of open ended questionnaires in her/his teaching activity