Building a Better Enterprise

Until recently, data automation in school districts centered around one application—the student information system. Data from various sources, including classrooms, central offices, libraries, and cafeterias, would flow in and out of the SIS, helping to streamline day-to-day school management and coordinate state and federal reporting. Instructional systems, such as those for conducting formative assessments and delivering curriculum, sat apart from the SIS in their own information silos.

Today, however, this “classical” model is gradually being replaced. As districts struggle to meet No Child Left Behind requirements, improve instruction, and above all, raise student achievement, they’re asking for data to be synchronized across the various systems and accessible to all stakeholders. As a result, student data has suddenly moved to the center of the district enterprise, with the data warehouse facilitating its flow.

Here’s a sample “student-centered enterprise” scenario. A math teacher is working at home on her lesson for the next day. She logs in to the district’s instructional management system and opens up the lesson plan generation tool. Meanwhile, she simultaneously has access to demographic, grade, and assessment data for each student— information that’s being fed to her from the district’s data warehouse. Armed with this collection of data, along with current knowledge about her students’ strengths and weaknesses, the teacher then selects appropriate activities and resources. The result: a data-informed lesson that individualizes instruction for each student.

The previous example illustrates how teaching and learning can be enhanced when traditional silos of information are linked together and pushed to users in a unified way rather than pulled haphazardly from various systems. For most school districts this represents an enormous paradigm shift, one that requires a rock-solid vision and strategy to execute successfully.


Before looking at how districts might go about moving from a classical to a student-centered enterprise, here is a breakdown of the differences between the two approaches.

  • Classical:
  • Student-Centered:
  • Student information system at the center of data automation
  • Systems stand alone and gather information separately from each other
  • Focus of data typically at building level with central administration
  • Relevant student information manually duplicated throughout various systems, burning up an enormous amount of resources and negatively impacting data quality
  • Data for individual students cannot be imported or exported in real time; in most cases districts have to go through the unwieldy process of exporting information for the entire student body all at once (also known as batch transfer)
  • No data modifications from external sources accepted; students and parents can’t remotely log on and enter change of- address information into the system
  • Assessment systems might consist of a traditional grade book, homework, and teachers’ qualitative observations about students
  • Self-contained curriculum products and resources aren’t able to interact with other systems on the enterprise; for example, standalone math software that uses an internally developed rubric that is not correlated to the actual curriculum
  • Data warehouse at core of data automation
  • Automated free flow of student information across the entire enterprise
  • When data—for example, assessment results—is added or changed this information is automatically updated wherever it appears in the enterprise
  • Data about individual students can be transferred in real time
  • Outside stakeholders can access relevant information and make modifications (where they have clearance to do so)
  • Assessment system provides educators with immediate feedback on student progress; for instance, teachers might give students a five-question quiz that’s scanned into an assessment management system, with results being immediately tabulated and electronically pushed to a portal interface for each educator
  • Curriculum solutions integrated with the enterprise; for example, reading software that uses externally gathered performance data (in addition to internally developed rubrics) to gauge student achievement and adjust instruction accordingly
  • Curriculum and accompanying resources are dynamically linked and keyword-searchable through a universal content-neutral interface
  • Metadata architecture establishes a baseline for longitudinal evaluation; metadata is data about the data, such as who authored it, what kind of condition it’s in, who has access to it, and other characteristics
  • Business intelligence tools allow data from different systems and external sources to be compared and contrasted to each other, such as analyzing the relationship between attendance, gifted programs, socioeconomic status, and achievement
  1. Student Information System
    The SIS primarily handles student demographic data, registration, scheduling, attendance, and grades. Common add-on modules and separate subsystems help districts manage cafeteria, transportation, library, and independent education plans, as well as health records and conduct reports.
  2. Assessment Management System
    An AMS measures student performance, gauges strengths and weaknesses, and provides feedback to educators at the classroom, building, and district level.
  3. Learning Management System
    The LMS delivers multimedia resources, such as educational Web sites, and computer-based instructional tools, such as core curriculum software packages.
  4. Instructional Management System
    The IMS supports the automation of a district’s curriculum, standards, lesson plans, and their respective scope and sequence. Note: Sometimes districts will integrate an assessment reporting and tracking tool into the IMS.