Digication enables authentic program and institutional level assessments by archiving ePortfolio-based student work and enabling complex statistical analyses of the archived ePortfolios. The assessment process involves several steps that tie the initial stages of student work collection to the final stage of reporting on the institution’s or a program’s learning outcomes.
The first step in any assessment process is constituted by the collection of student ePortfolios or other type of file submissions. This is of course necessary to have an adequate sample of student work on which statistical analyses can be run and which can yield accurate information about the status of a program.
Digication permits students to integrate in their ePortfolios materials in a variety of formats, e.g. rich text, image, audio, video. Therefore, students have significant freedom in demonstrating their creativity, skills and competencies, and faculty can stimulate students to respond to assignments by taking advantage of the capabilities of the platform.
Digication’s flexibility allows any of the student uploaded materials to become evidence in learning assessment processes. Assessments can target whole student ePortfolios, particular ePortfolio pages, or just specific responses to assignments, such as a comment or a text document. Once a piece of learning evidence is uploaded, it is immediately archived, time-stamped, and assigned a submission number. This way student submission-patterns can be easily tracked, and the assessment system has a reliable log of student work to which assessors can revert when needed.
The next stage of the assessment process involves the assignment of student submissions to the reviewer(s) tasked with assessing the student work. The assignments can be randomized and anonymous in order to ensure the highest degree of objectivity in the assessment process. The Digication system permits assessment of the same ePortfolio (or file submission) by more than one reviewer at any given time. If assessment scores prove to be contentious at any point in the process, the disputed submissions can be assigned to yet another reviewer who can re-evaluate the work and ensure that its evaluation meets objective
standards.
The process of student work evaluation requires reviewers to define the relevant learning rubrics in light of which submissions are assessed, or for such rubrics to be created by administrators beforehand. Administrators can set up the assessment system by logging in the Digication Assessment Management System and creating the relevant rubrics for assessment. Alternatively, administrators can request the Digication team build the needed rubrics by providing Digication with the desired content of the rubrics.
Once the assessment rubrics are defined, reviewers can start the evaluation processes. Reviewers need only to log in to their home page to view the submissions assigned to them and proceed to score the submitted work and to comment on it, making sure to save in the end their scoring and comments. The submitted work can be assessed relative to the previously specified learning rubrics, and can be organized in function of other kinds of categories, such as: submission period (e.g. a given semester), the program for which they are submitted, student name, assignment type, given major or given cohort, course number and so on.
The various categories of assessment and organization of data can be aggregated further for obtaining sophisticated statistical insights about learning outcomes. This way, reviewers can assess a particular student submission, for instance, to determine its quality as a piece of critical thinking, can compare different cohorts’ critical thinking outcomes, or can focus on evaluating a cohort’s critical thinking outcomes in a given semester.
After reviewers complete the evaluation of the submissions assigned to them, the scored assessments are collected in a spreadsheet report. The spreadsheet can be exported as a CSV file so that administrators may inform the school of the scores for the different categories of data. The capability of aggregating the data collected from student work based on a variety of criteria and easily viewing them in the spreadsheet provides administrators with the best evidence for developing reports on student learning outcomes and program and institutional performance.
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