Data Systems Standards and Guidelines from the National Center for Education Statistics

If you are involved in data-driven decision making in your school or school district, it is important to keep up with the most recent standards regarding data systems. The National Center for Education Statistics has recently developed a toolbox for educational data system designers and managers who are "looking for ways to build and/or improve education data systems".

According to the NCES website, the Education Data Model, Version I is a "comprehensive, localized, conceptual model that provides a generic blueprint for schools and districts. This blueprint enables schools to evaluate and improve instructional tools, communicate those needs to their umbrella agency or directly to vendors, enhance the movement of student information from one district to another, and in the end, have better tools to inform instruction. Using a standard Education Data Model as a starting point contributes to a comprehensive understanding of the need for data, how data are used, and the questions that can be answered with the data. For instance, the Data Model helps to answer questions such as the following:

• What data do schools, LEAs, and states need to collect and manage at the local level to meet the information needs of students, staff, and other stakeholders?
• What data do they need to effectively manage education organizations in order to increase success in teaching, learning, and school leadership?
• What data do they need to efficiently manage and run an education organization from a fiscal and administrative perspective?

A single, comprehensive model of education data is prerequisite to establishing automated systems with the right data, data that are comparable across time and systems, and data accurate enough to answer our questions".

Educational data systems are developed on a large scale, and generally the "client" is a school district, or administrator of a school district. I am not sure that those who design the data base systems are aware of the work of school psychologists, and how our work is negatively impacted by a system that doesn't address our work needs efficiently or effectively.

So what is a data-minded school psychologist to do? The first step is to become informed about databases and how they are used and implemented in your school(s). Find out who is responsible for making decisions regarding the use of data-based systems, and find out if there is a district committee who is involved in this area. It just might be that it has not occurred to high-level administrators that school psychologists might want to have a say in this matt

If you are interested learning more, you can browse the data model on the NCES Data Model web page. Also take a look at the "How to Use the Data Model" on-line guide.

Here are a few graphics from the NCES website:

Concept map behind the development of the data model:



Taxonomy - entities, classes, and attributes:



Here is the relationship diagram of the data model:


Educational data systems are developed on a large scale, and generally the "client" is a school district, or administrator of a school district. I am not sure that those who design the data base systems are aware of the work of school psychologists, and how our work is negatively impacted by a system that doesn't address our work needs efficiently or effectively.

So what is a data-minded school psychologist to do? The first step is to become informed about databases and how they are used and implemented in your school(s). Find out who is responsible for making decisions regarding the use of data-based systems, and find out if there is a district committee who is involved in this area. It just might be that it has not occurred to high-level administrators that school psychologists might want to have a say in this matter.

Announcement: 14th International Conference on Artificial Intelligence in Education

If you area interested in technology, psychology, and education, you might also be interested in the 14th International Conference on Artificial Intelligence in Education.

From the conference website:

July 6th - 10th 2009, Thistle Hotel, Brighton, UK
http://www.aied2009.com
held in cooperation with AAAI

"AIED 09 will focus on the theme "Building Learning Systems that Care: From Knowledge Representation to Affective Modeling". This extends an AIED vision proposed some 20 years ago by John Self. The field has moved a long way since then. It is now widely accepted that effective learning environments are expected to care about both learners and tutors, and to have a good understanding of the variety of learning contexts. The key research question now is how to tackle the complex issues related to building learning systems that care, ranging from representing knowledge and context to modeling social, cognitive, metacognitive, and affective dimensions. This requires linking theory and technology from artificial intelligence, cognitive science, and computer science with theory and practice from education and social science."

The Proceedings will be published by IOS Press in the Frontiers in Artificial Intelligence and Application series.

"The International Conference on Artificial Intelligence in Education is part of an ongoing series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. The conference provides opportunities for the cross-fertilization of techniques from many fields that make up this interdisciplinary research area, including: artificial intelligence, computer science, cognitive and learning sciences, education, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which AIED systems have been designed and evaluated."


IMPORTANT DATES

* Papers, posters, YRT/DC: 15 Jan 2009 (11:59 pm Hawaii)
* Camera ready due: 15 April 2009
* Author notification: 16 March 2009
* Workshops, panels, interactive events and tutorials proposals: 15 Jan
2009 (11:59 pm Hawaii)
* Workshops, panels, tutorials and Interactive Events approved: 20
February 2009
* Conference: 6-10 July 2009


INVITED SPEAKERS
* Prof. Susanne P. Lajoie, McGill University, Canada
* Prof. Kenneth D. Forbus, Northwestern University, USA
* Prof. Wolfgang Nejdl, Distributed Systems Institute, Hannover, Germany


TOPICS
Topics of interest to the conference include, but are not limited to:

1. Modeling and Representation
------------------------------
* Models of learners, facilitators, tasks and problem-solving processes
* Models of groups and communities for learning
* Modeling of learning contexts
* Modeling of motivation, metacognition, and affect aspects of learning
* Ontological modeling
* Dealing with learner dynamics
* Handling uncertainty and multiple perspectives
* Representing and analyzing discourse during learning

2. Models of Learning
---------------------
* Intelligent tutoring and scaffolding
* Intelligent games for learning
* Motivational diagnosis and feedback
* Interactive pedagogical agents and learning companions
* Agents that promote metacognition, motivation, and affect
* Adaptive question-answering
* Multi-agent architectures

3. Intelligent Technologies for Learning
----------------------------------------
* Natural language processing
* Data mining and machine learning
* Knowledge representation and reasoning
* Semantic web technologies and standards
* Social recommendations
* Social networks

4. Pedagogical Models
---------------------
* Inquiry learning
* Social dimensions of learning
* Social-historical-cultural contexts
* Informal learning environments
* Communities of practice

5. Learning Contexts and Domains
--------------------------------
* Learning in open web environments
* Collaborative and group learning
* Simulation-based learning
* Ubiquitous learning environments
* Learning grid
* Lifelong and workplace learning
* Domain-specific learning applications, e.g. language, mathematics,
science, medicine, military, and industry.

6. Evaluation
-------------
* Human-computer interaction
* Evaluation methodologies
* Experiences and lessons learned


SUBMISSION CATEGORIES
* Full papers: original and unpublished work
* Young researcher's track (YRT) and Doctoral Consortium (DC): work-in
progress by graduate students and other young researchers
* Posters: work-in-progress
* Interactive events (IE): demonstration of AIED systems
* Workshop proposals: address emerging topics in AIED
* Tutorial proposals: give overview of important AIED topics
* Panels: bring together experts to discuss AIED directions

Submission instructions are available at
http://www.aied2009.com


CONFERENCE ORGANIZATION

* Conference Chair: Art Graesser
* Local Arrangements Chair: Ben Du Boulay
* Program Chairs: Vania Dimitrova and Riichiro Mizoguchi
* YRT Chairs: George Magoulas and Tanja Mitrovic
* Poster Chairs: Neil Heffernan and Tsukasa Hirashima
* Interactive Events Chairs: Jack Mostow and Katy Howland
* Workshop Chairs: Scotty Craig and Darina Dicheva
* Tutorial Chairs: Beatriz Barros and Stephan Weibelzahl
* Sponsorship Chairs: Roger Azevedo and Rose Luckin
* Publicity Chair: Genaro Rebolledo Mendez

Via Genaro Rebolledo Menez, from the EDM (Educational Data Mining) listserv

RELATED:
Educational Data Mining Resources from the EDM website:

Carnegie Mellon University's PROJECT Listen has released the Bayes Net Toolkit for Student Modeling, a system which makes it easier to useBayes Nets and Bayesian Knowledge-Tracing to model student data.

The Pittsburgh Science of Learning Center offers DataShop, a system which you can use to conduct learning curve analysis on educational data.

SymTrend: Use of a PDA for tracking progress for children and adults with Asperger Syndrome and other disorders

I'm always on the lookout for applications that can support intervention and progress monitoring. SymTrend is a company that provides coaching and monitoring software for a variety of social and emotional difficulties and disorders. SymTrend looks like it has potential for intervention and progress monitoring in schools for RTI (Response to Intervention), Positive Behavior Intervention and Supports, and IEP's.

The beauty of SymTrend, in my opinion, is that it helps people develop self-monitoring skills through providing a means of analyzing data that is gathered frequently. From what I understand, through interaction with the software, the student/client establishes a better understanding of themselves, and also and understanding of feelings, triggers, reactions, and coping strategies. A rich amount of data is collected that can be helpful to treatment providers, or special educators.

The following video from Minna Levine, Ph.D., president of SymTrend, explains how it can be used for young people who have Asperger syndrome:



Information I "reblogged" Dan Brickland, a SymTrend Advocate:

"SymTrend is an electronic diary system that is designed to optimize symptom and behavior reporting, progress tracking, and session to session progress. It combines tracking tools to see how things are going, with analytic tools for seeing what might subvert or retard treatment efficacy. It also contains guidance tools that can help make things go better. SymTrend is most useful when one or more of the following occur in a health or educational challenge:

• The course of change is slow and the indices of progress may be mixed or ambiguous.
• There is no single magic bullet solution or cure.
• There are, instead, multiple solution strategies that can be tried.
• The best combination of solution strategies depends on individual circumstances.
• The delivery of multiple services occurs at different sites and requires some coordination in time or over developmental stages.
• The road to success has hidden mine fields that impede progress, must be located, and that must be circumvented.
• The indices of progress - symptom reduction and skill building - are best measured at home or in the community not in an office.
• Progress indices change through out the day or from day to day in response to events.
• Verbal report is compromised by observational and memory failure.
• The verbal report takes longer than the service provider can give to listen.
• The person with the problem would benefit from on the spot "when to" reminders to improve progress.
• The person with the problem would benefit from how to reminders which enhance presence of mind and executive functioning reminders to improve progress."

-From "My Take on SymTrend"

If you are using SymTrend in the schools, clinical practice, or for research, please leave a comment!

Data-Driven Decision-Making and Educational Data Mining

Technology tools are needed in order to support efforts such as Response to Intervention (RTI) that rely on closer monitoring of data regarding student progress. The Winston-Salem school district in North Carolina has implemented a web-based application known as the Teacher's Workbench, funded in part by a Reinventing Education grant from IBM.

According to an abstract by Mark Singley, Richard Boehme, Lei Kuang, Richard Lam, IBM T.J. Watson Research Center, USA , "Teacher’s Workbench is a web application whose goal is to improve day-to-day instructional decision making by providing teachers with a finer-grained, more timely understanding of the ever-changing patterns of student proficiency in their classrooms. Teacher’s Workbench takes a three-pronged approach: First, the system provides integrated support for managing standards-based classroom data through the core functionality of a teacher planbook, student profiler, and access to third-party gradebooks. Secondly, the system amplifies the teacher’s ability to analyze and understand student performance by mining the gradebook, planbook, and other school data sources. The system alerts teachers to the existence of critical teaching and learning patterns. Finally, the system helps teachers act on these new understandings by automatically locating and delivering instructional resources in response to the patterns detected."

Business Tools for Better Schools is a website that advocates for improving educational data systems:

"...too often, educators do not know how to use the data system or lack training in how to leverage the information to improve instruction. Although collecting and disseminating better data is essential, knowing how to analyze and apply this information is just as important for improving student achievement. Business leaders, by tapping into their own corporate experiences, can help educators, administrators and policymakers understand how to access and use longitudinal data as part of daily operations and long-term improvement strategies."

In my opinion, school psychologists, given their backgrounds in measurement and data analysis, should be part of the decision-making process when school districts adopt new data systems designed to enhance student progress-monitoring.

If you are a school psychologist or educator who is involved in the use of data-driven decision-making to support Response to Intervention efforts, please leave a comment. What sort of software does your school use? What security and privacy precautions do you have in place to ensure the confidentiality of student information?