Fairness

Validity

Reliability

Bias

All students should have an equal opportunity to succeed.

The test should be free from bias.

The test should be valid.

All of the above

Validity refers to the accuracy of a measurement, while bias refers to the systematic error in a measurement.

Validity refers to the fairness of a measurement, while bias refers to the accuracy of a measurement.

Validity refers to the reliability of a measurement, while bias refers to the fairness of a measurement.

None of the above

Cultural bias

Gender bias

Socioeconomic bias

All of the above

Use clear and unambiguous language.

Avoid stereotypes and generalizations.

Provide equal opportunities for all students.

All of the above

Educational measurement data can be used to make decisions about students.

Educational measurement data can be used to identify students who need additional support.

Educational measurement data can be used to track student progress.

All of the above

Educational measurement data can be used to discriminate against students.

Educational measurement data can be used to invade students' privacy.

Educational measurement data can be used to label students.

All of the above

Obtain informed consent from students and parents.

Use data only for the purposes for which it was collected.

Protect the confidentiality of student data.

All of the above

Professional organizations can develop ethical guidelines for the use of educational measurement data.

Professional organizations can provide training on the ethical use of educational measurement data.

Professional organizations can advocate for the ethical use of educational measurement data.

All of the above

Individual educators can use educational measurement data in a responsible and ethical manner.

Individual educators can advocate for the ethical use of educational measurement data.

Individual educators can educate students and parents about the ethical use of educational measurement data.

All of the above

Lack of awareness of ethical issues in educational measurement

Lack of resources to support ethical practices

Competing priorities

All of the above

Provide training on ethical issues in educational measurement.

Develop resources to support ethical practices.

Create a culture of ethical decision-making.

All of the above

Ethical issues in educational measurement will become more complex as technology advances.

The increasing use of data in education will raise new ethical challenges.

Educators will need to be prepared to address ethical issues in educational measurement.

All of the above

AI systems may be biased against certain groups of students.

AI systems may be used to make decisions about students without human oversight.

AI systems may be used to track students' online activity without their consent.

All of the above

Develop ethical guidelines for the use of AI in educational measurement.

Provide training on the ethical use of AI in educational measurement.

Create a culture of ethical decision-making around the use of AI in educational measurement.

All of the above