Learning Objects: Bloom’s Taxonomy and Deeper Learning Principles
Patricia McGee
Department of Interdisciplinary Studies & Curriculum and Instruction
The University of Texas at San Antonio
USA
pmcgee@utsa.edu
Abstract. Learning objects cover a wide range of designs, applications, and assessments. This
paper examines the relationship between Bloom’s Taxonomy and deeper learning principles
and examines how objects may support knowledge acquisition by design.
Learning objects trigger debate and discussion: what are they, how should they be designed and used, how
do we keep track of them, and who owns them. Although there is not a consensus about what a learning object is,
the idea behind them is familiar to faculty and instructional designers who make objects and reuse them regularly.
Packaging content so that it can be re-used applies to a variety of learning materials such as educational books,
overhead slides, video, and computer software. Over time, practitioners developed pedagogies for each of these
instructional tools to best use them to achieve learning objectives. Although learning objects and repositories are
increasing in number, a well-articulated set of principles, guidelines, or model for their instructional use has yet to
emerge. This paper illustrates the relationship between deeper learning as it relates to Bloom’s Taxonomy as related
to object granularity. Additionally it identifies ways of thinking and learning that may be implied by deeper learning
principles but are not directed addressed in Bloom’s Taxonomy.
Deeper learning
Research about learning is directing us to deeper learning principles or DLP (see Dabbagh, 2003; Carmean,
2002; Weigel, 2002; American Psychological Association, 1997). Deeper learning engages the learner who actively
explores, reflects, and produces knowledge rather than recalls and regurgitates. These principles are derived from
learning theory and research and build on the learner’s knowledge base that is acquired prior to or as a part of more
complex learning experiences as prescribed by deeper learning. We can’t problem solve or investigate without
having basic knowledge that allows us to make connections between similar or dissimilar ideas, problem solve,
make decisions, etc. Careful examination of deeper learning principles reveals that they do not address the
fundamental knowledge that is requisite for the more complex actions that they prescribe, see Table 1, A
Comparison of Deeper Learning Principles.
Carmean
Dabbagh
Active learning involves solving realworld problems; using judgment and
exploration; situated in action; emphasis
on practice and reinforcement;
involvement in real-world
Authentic learning focuses on real
world and complex problems that are
interdisciplinary, occur over long
periods of time and involve a range of
learning materials and resources
Learning that is social provides
opportunities for cognitive
apprenticeship; reciprocity and
cooperation among students; prompt
feedback; encouragement of contact
between student and faculty; emphasis
on rich, timely feedback.
Contextualized learning builds on
existing knowledge and is integrated
into the learner's world; knowledge is
demonstrated; deep foundation of
factual knowledge; consideration of
leaner preconceptions; focus on how the
world works; facts and ideas in the
Dialogue facilitate articulation,
collaboration, reflection
Guidance in learning is built on
modeling, scaffolding, coaching
Weigel
Communities of inquiry support habits
of mind, interactions, and negotiation of
knowledge.
Conditionalized knowledge “specifies
the contexts in which it is useful” (p. 6).
context of a conceptual framework;
concrete rather than abstract.
Engaged learning addresses diverse
talents and ways of learning; high
expectations; high-challenge, low-threat
environments; intrinsic motivators and
natural curiosities.
Learning encourages ownership so that
learners can organize knowledge in
ways that facilitate retrieval and
application; learner control of own
learning; time on task; learner
independence and choice; time for
reflection; higher order thinking
Exploration involves problem solving,
hypothesizing, inquiring, role-paying
Self-directed learning promotes selfawareness and regulation
Metacognition involves thinking about
thinking as a strategy to analyze
understanding and adjusting learning
strategies then learning is not achieved.
Table 1: A Comparison of Deeper Learning Principles
It is important to keep in mind that the DLP are not progressive but rather symbiotic. Learners may enter a learning
activity in different ways through different points of engagement. If we take Carmean’s typology, we might
organized them in the following manner.
Social
Ownership
Active
DLPs
Contextual
Engaged
Bloom’s Taxonomy
Bloom’s Taxonomy has, in the past, provided a foundation for developing learning objectives designed for
learners to acquire knowledge, although it was originally designed as an assessment tool. Regardless of its intended
purpose, it has been used for a variety of purposes across the learning spectrum: K-12, post-secondary, military, and
workplace (see Anderson, & Krathworhl, 2001; Gooden, Gelosh, Hazard, Vombrock, Pisel, Shulson, Landers, &
Sharp, 1998; Phillips, 1998). Although not a pedagogical tool, by virtue that each level describes what the learner
should be doing, Bloom’s Taxonomy can be viewed as a pedagogical instrument in the design of instruction and it
has been used as such. Although originally addressing three learning domains – cognitive, affective, and
psychomotor -- the revised taxonomy (Anderson, & Krathworhl, 2001), used as a reference here, only addresses the
cognitive domain and adds a content dimension. Bloom’s Taxonomy is designed to build content knowledge from
basic foundations – remembering – to more complex manipulation of content – creating. In this way the learner
acquires knowledge that is appropriate for their entry level of existing knowledge. The greater the prior knowledge,
the higher level that learning experiences can be designed. This paper does not suggest that Bloom’s Taxonomy
should be used as a pedagogical instrument but rather that it has provided a conceptual framework for learning that
has been adopted in almost all environments in which learning occurs. This may be an influence of it’s initial
adoption by K-12 education and instructional systems design. Regardless, it is important to acknowledge that
instruction has and is being designed around this framework.
The deeper learning principles mapped to the revised taxonomy reveals missing conditions for deeper
learning, see Table 2 Revised Bloom’s Taxonomy, Condensed, and Deeper Learning Principles.
Factual knowledge
Conceptual
Procedural
Meta-cognitive
knowledge
1. Remember
2. Understand
3. Apply
4.Analyze
5.Evaluate
6.Create
Knowledge
Knowledge
Contextualized
Active
Engaged
Ownership
Table 2: Revised Bloom’s Taxonomy, Condensed, and Deeper Learning Principles
Utilizing the DLP and the taxonomy to guide instructional design suggests several assumptions. First, instruction
developed from the DLP must consider the prior knowledge of the learner of it is possible that learners will enter
into a learning experiences either without the requisite skills or knowledge base or that the activity begins with too
much basic knowledge preparation. Second, Bloom’s taxonomy, as it stands alone, does not account for interactions
among learners, a fundamental and reacuring element in the DLP. Finally, there is a disconnect between the
metatcognitive aspects of learning which are suggested by the taxonomy and situated in process while more integral
to all aspects of learning according to DLP. Considering the use of Bloom’s taxonomy in K-12 education and
instructional design models, and a movement toward DLP in K-16 education, the resolution and integration of these
two sets of principles hold implications for the burgeoning development of learning objects.
Learning Objects
Within online learning environments there may be certain assumptions about what should take place and
what needs to be learned. As research indicates, a social and interactive environment best supports online learning
(ADEC, 2001) but this type of interaction may not be necessary or appropriate for learning introductory content:
concepts, processes, principles, or facts. Learning objects may be able to address this challenge through the design
complex online learning experiences, as situated in or around learning objects.
Wiley and others have discussed the granularity of objects from the small (an asset) to the complex (a
course). Wiley, Gibbons, and Recker (2000), Quinn & Hobbs (2000), and Longmire (2000) discuss the apparent
fact that the smaller a learning object is the more likely that it (a) can be re-used and (b) can be used within an
adaptive learning environment. South and Monson (2001) discuss granularity in terns of re-usability in that with
100% granularity, the learning purpose disappears and its value to instructional is questionable, where if there is
0% granularity (as in a specific and well articulated course) content is so contextually bound that reusability is
difficult if not impractical. Wiley, Gibbons, and Recker (2002) address issues of granularity and how these relate to
instruction. They argue that granularity is related to how learning objects are combined, and that more complex
objects are, the more challenging it is to combine them because of the multiple layers of elements in the design of
the object, e.g. instructional approach, learning design, or even logic of the system within which the object operates.
Reigluth and Nelown (1997 as cited in Wiley, 2000) observe that educators break down instructional
content into sub-parts when planning for instruction, and Wiley suggests that this transfer to the notion of 100%
granular learning objects; the chunking of content to its smallest parts. Courses then, at a low level of granularity
may be combinations of chunked information, at least in theoretical discussions of learning object use.. Most
instructional design models require content that is chunked, making them an easy fit when designing a manageable
and reusable object. However, this suggests that content can be reduced to small chunks and support learning, which
reflects an approach to learning as conceptualized in Bloom’s taxonomy but is contrary to deeper learning
principles.
Factual
Remember
1
Ingredients
and
conditions
necessary
Topic: How Jelly Beans are Made1
Bloom’s Taxonomy
Conceptual
Procedural
Metacognitive
Processes that are
unique
Identification
of generic
steps
Record steps in
the way that
you can best
remember
Deeper Learning Principles
Active
Develop a recipe for a
new type of jelly bean
Inspired by the Alliance for Innovative Manufacturing at Stanford University’s learning objects on How Everyday
Things are Made, http://manufacturing.stanford.edu/
Understand
Ingredients
Compare
process/ingredients
to gummy bears
Draw flow
chart of steps
Identify another
processes that
you have used
similar to this
one
Social
Apply
Make jelly
beans
Make gummy
bears
Test chart by
making
chocolate
drops
Decide whether
following steps
is helpful to
you
Contextual
Analyze
Compare
results to
machine
made jelly
beans
Explain what
would happen
if ingredients
were
substituted
Compare jelly
beans to gummy
bears that you
made
Identify
major steps
and sub-steps
and illustrate
Engaged
Determine why
results didn’t
match machinemade results
Identify other
candies that
could be
made using
this process
Ownership
Create a
recipe for a
new flavor
of jelly bean
Create a recipe
for making a
new candy
Design a
home-made
system
Evaluate
Create
Interview a jelly bean
manufacturer, organize
a design team,
determine the
attributes of the new
bean
Identify the processes
and ingredient,
determine a flavor that
would appeal to the
market
Design promotion
materials to appeal to a
variety of audiences.
Create timeline,
determine roles,
establish quality
controls, and periods
for review
Bloom’s and deeper learning
How and why learning objects are used is still unclear as most repositories or providers are not
documenting (or sharing the documentation) of how, why and by whom they are used. It may be that a taxonomy of
learning object pedagogy, drawing from Wiley’s (2000) taxonomy of learning objects and Bloom’s Taxonomy for
Teaching and Assessing (Anderson & Krathwohl, 2001), may guide and serve a useful function in instructional
design and implementation (i.e. teaching and learning).
Dabbagh (2003) illustrates the relationship between what instructional strategies (what the teacher does)
and learning strategies (what the learner does) as does Weigel (2002). The comparison of the deeper learning
principles with Bloom’s Taxonomy (see Table 3) then focuses on what the learner does rather than what the
instructor does (instructional strategy or pedagogy). For illustration purposes a link to an object that illustrates each
level of Bloom’s Taxonomy is provided.
Bloom’s Taxonomy
Deeper Learning Principles
(Carmean)
Deep Learning (Weigel)
Remembering
Contextual: build on
knowledge base; built in
facts
Contextual: knowledge is
demonstrated; concrete
rather than abstract
Ownership: organizing for
retrieval
Active: situated in action
contextual: knowledge is
demonstrated
Active: real world
problems
“relate to previous
knowledge and
experience” (p.6)
“aware of understanding
that develops while
learning” (p.6)
Understanding
Applying
Analyzing
Evaluating
Active: intertwined with
judgment and exploration
Ownership: higher order
thinking
“look for patterns and
underlying principles”
(p.6)
“look for patterns and
underlying principles”
(p.6)
“check evidence and relate
to conclusions” (p. 6)
“examine logic and
argument cautiously and
Deep Learning (from
Instructional Strategies)
(Dabbagh)
authentic: multiple knowledge
domains and skills
Exploration: role playing
authentic: ill-defined and
complex
Authentic: real word; variety of
resources
Exploration: hypothesizing
Creating
Ownership: failures,
planning ahead,
apportioning time and
memory to tasks
Ownership: independence
and choice; higher order
thinking
critically” (p. 6)
Problem solving
Exploration
Exploration: problem solving
Table 3: Bloom’s Taxonomy and Deeper Learning
Each level of the taxonomy is reflected in at least one deeper learning principle. However, many deeper learning
principles do not correspond to the taxonomy and which are problematic in objects with high granularity, see Table
4, The Missing Principles. The DLP represent aspects of teaching and learning that are difficult to map to learning
objects: the blurring line between the roles and behaviors of teachers and learners.
Carmean
Social
Contextual
Engagement
Ownership
Cognitive apprenticeship
Cooperation
Prompt feedback
Student-instructor interaction
Integrated into learner’s world
How the world works
Recognizing diverse talents and ways of
learning
High expectations
Low threat
Intrinsic motivation
Weigel
Cognitive apprenticeship; scaffolding
Dabbagh
Guidance: scaffolding
Exploratory: collaboration
Modeling
Guidance: modeling
Coaching
Guidance: coaching
Authentic: real world
Self-awareness of learning
style
“Actively interested in course content
(P. 6)”
Time on task
Articulation
Key
Instructor
Exploration: articulation
Instructor or Learning
Learner
Table 4: The missing principles
Lee Shulman (2002) argues for a revised taxonomy that addresses a more constructivist approach to teaching and
learning as implied by the DLP. His table of learning is not situated in a hierarchy. A comparison of the three
typologies presented in this paper reveals that to some extent they overlap at least and at best they corroborate the
conditions necessary for learning. Each typology must be viewed with the understanding that learning, in
formallearning environments, requires instructional planning and intentional designs that support interactions
among learner and instructor, as reflected in the DLP. It may be that the most critical of these principals is situated
in the practices and actions of the instructor, that of engagement.
Table of Learning
Deeper Learning Principles
Bloom’s Taxonomy
Engagement and Motivation
Engaged
Evaluation & Create - Metacognitive
Knowledge and Understanding
Ownership
Knowledge & Comprehension – fact,
concept, procedure
Performance and Action
Active
Analyze - fact, concept, procedure
Reflection and Critique
Ownership
Evaluation
Judgment and Design
Commitment and Identity
Contextual & Active
Ownership
Evaluation & Create
Evaluation & Create - Metacognitive
Shulman believes that learning begins with engagement as conceived in Edgerton’s work on “pedagogies
of engagement.” Engagement may indicate a variety of approaches to providing for learning in terms of being
cognitively engaged (I understand and want to know more), physiologically engaged (I am paying attention),
emotionally engaged (I have a vested interest), or strategically engaged (I am in ‘in the action”). Evoking
engagement in a learning object design is a challenge; each learner may have different ways they are engaged.
Additionally, the learning experiences that are wrapped around, proceed, or follow a learning object interaction may
effect the engagement of the learner.
The principles suggested by the DLP but not directly addressed by Shulman or Bloom indicate the blurring
or roles in the emerging learning models. Instructor responsiveness to individual learners through modeling,s
caffolding, expectations, and feedback cannot be separated from a learning activity and therefore are necessarily
situated in learning principles and not segregated to teaching principles. Although these may be supported through
instructional strategies it is difficult if not impossible to design for the missing principles without systems that can
provide individualized feedback and interaction that is personalized, responsive, and immediate.
Implications for learning objects
If learning objects are designed to support progressively complex knowledge construction, they must be designed
around principles that are known to build intellectual capital. Bloom’s and Shulman’s taxonomy, framed within the
DLP, are one example of a conceptual framework. Without this starting place a learning object is no different than a
learning asset – there is no assurance that anyone will learn anything. It make be that many of the conditions that
support learning are wrapped around assets or objects, either in containers as can be seen in the Instructional
Architect (http://ia.usu.edu/), the technology-mediated environments of Learning Course Management Systems or
co-joined communications and learning tools, (e.g., Fle3 http://fle3.uiah.fi/, blogs, Wikis, etc.), or in the activities
that occur in face-to-face environments.
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