د/ايمان زغلول قاسم

استاذ تكنولوجيا التعليم المساعد بكلية التربية بالزلفي

book B95

individual activity.
In constructivism, learning is seen as a cyclic process in which new knowledge and
skills are built on prior ones through continuous adaption of the learning environment to the
learners‘ needs (Jonassen, 1991; Stobart, 2008). In social constructivism, the learners‘ active
role is emphasised, and teachers are expected to actively engage learners in constructing
knowledge and developing skills by frequently providing elaborated feedback. Collaborative
learning and solving real-world problems, which use peer feedback as an important learning
mechanism, characterise social constructivist learning environments (Lesgold, 2004; Stobart,
2008; Thurlings et al., 2013).
7.2 Theoretical Framework
First, this paper discusses the theoretical underpinnings of each approach in terms of
its origin, definition, goals, and relation with the five learning theories. This is followed by a
description of the implementation of each approach in terms of aggregation level, assessment
methods, and feedback loops.
7.2.1 Theoretical Underpinnings of DBDM
Teachers usually make instructional decisions intuitively (Ingram, Louis, & Schroeder,
2004; Slavin, 2002, 2003). However, educational policies such as No Child Left Behind
(NCLB) have caused an increase in accountability requirements, which has stimulated the use
of data for informing school practice in the USA (Wayman, Jimerson, & Cho, 2012). Using
data to inform decisions in the school is referred to as DBDM (Ledoux, Blok, Boogaard, &
Krüger, 2009). Schildkamp and Kuiper (2010) defined DBDM as ―systematically analyzing
existing data sources within the school, applying outcomes of analyses to innovate teaching,
curricula, and school performance, and, implementing (e.g., genuine improvement actions)
and evaluating these innovations‖ (p. 482). The definition of data in the context of schools is
―information that is systematically collected and organized to represent some aspect of
schooling‖ (Lai & Schildkamp, 2013, p. 10). This definition is broad and includes any
relevant information derived from qualitative and quantitative measurements (Lai &
Schildkamp, 2013; Wayman et al., 2012).
Data include not only assessment results, but also other data types, such as student
background characteristics. Data use can be described as a complex and interpretive process,
in which data have to be identified, collected, analysed, and interpreted to become meaningful
and useful for actions (Coburn, Toure, & Yamashita, 2009; Coburn & Turner, 2012). The
action‘s impact is evaluated by gathering new data, which creates a feedback loop
(Mandinach & Jackson, 2012).
Early initiatives of DBDM were based on neo-behaviourism and cognitivism (Stobart,
2008), which meant that no explicit attention was paid to the sociocultural environment where
learning occurred. Previously, DBDM focused on reaching predetermined goals, checking if
the goals had been achieved, and adapting the learning environment where needed. This
process was mainly transmissive in nature, meaning that educational facilitators (e.g.,
teachers) were responsible for delivering adequate instruction to learners. In this view,
learning is an individual activity, and assessments are used to check on the individual
Chapter 7
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student‘s ability (Elwood, 2006). As a consequence of this view, assessment methods used for
DBDM, such as standardised tests, do not resemble characteristics of every possible learning
context in which the learner could have acquired that what is assessed.
However, lately DBDM seems to move more towards social cultural theory and
constructivism, which focuses on continuously adapting learning environments to facilitate
and optimise learning processes, taking into account learners‘ needs and individual
characteristics. Thus, instead of just acknowledging the context or controlling for it, the
emphasis is on the process of data use within a particular context (Coburn & Turner, 2011;
Schildkamp, Lai, & Earl, 2013; Supovitz, 2010).
By using data, teachers can set appropriate learning goals, given students‘ current
achievements. Subsequently, teachers can assess and monitor whether students are reaching
their goals, and if necessary, adjust their instruction (Bernhardt, 2003; Earl & Katz, 2006). In
this way, DBDM is used for formative assessment. The goal of using assessment data in
DBDM is almost always improving student achievement (Schildkamp et al., 2013)
Besides, data can be used for formative evaluation by school leaders and teachers for
policy development and school improvement planning, teacher development, and monitoring
the implementation of the school‘s goals (Schildkamp et al., 2013; Schildkamp & Kuiper,
2010).

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