The school improvement team decided to include a goal of decreasing chronic absenteeism to less than 5%. What type of decision-making does this represent?

The goal of decreasing chronic absenteeism to less than 5% reflects data-driven decision making because it is based on specific metrics and quantitative assessment of student attendance patterns. By using data, the school improvement team is identifying a measurable target that can guide their efforts and strategies to influence student attendance positively.

Data-driven decision making involves analyzing relevant data to inform actions and goals, ensuring that the decisions made are supported by empirical evidence rather than intuition or personal biases. This approach allows the team to assess current absenteeism rates, identify trends, and implement evidence-based practices aimed at reducing those rates effectively.

In contrast to other types of decision-making, such as subjective decision-making, which relies on personal opinions or feelings, or emotional decision-making, which may involve judgments based on feelings rather than facts, the focus on quantifiable outcomes in this context emphasizes the objective basis for the decisions being made. Random decision-making is typically characterized by a lack of systematic approach and disregard for data, which is not the case here.