B RIEFINGS IN BIOINF ORMATICS . VOL 14. NO 5. 648 ^ 660
Advance Access published on 10 May 2013
doi:10.1093/bib/bbt030
Integrating bioinformatics into senior
high school: design principles and
implications
Yossy Machluf and Anat Yarden
Submitted: 5th February 2013; Received (in revised form) : 4th April 2013
Abstract
Bioinformatics is an integral part of modern life sciences. It has revolutionized and redefined how research is carried
out and has had an enormous impact on biotechnology, medicine, agriculture and related areas. Yet, it is
only rarely integrated into high school teaching and learning programs, playing almost no role in preparing the
next generation of information-oriented citizens. Here, we describe the design principles of bioinformatics learning
environments, including our own, that are aimed at introducing bioinformatics into senior high school curricula
through engaging learners in scientifically authentic inquiry activities. We discuss the bioinformatics-related benefits
and challenges that high school teachers and students face in the course of the implementation process, in light
of previous studies and our own experience. Based on these lessons, we present a new approach for characterizing
the questions embedded in bioinformatics teaching and learning units, based on three criteria: the type of domainspecific knowledge required to answer each question (declarative knowledge, procedural knowledge, strategic
knowledge, situational knowledge), the scientific approach from which each question stems (biological, bioinformatics, a combination of the two) and the associated cognitive process dimension (remember, understand, apply,
analyze, evaluate, create). We demonstrate the feasibility of this approach using a learning environment, which
we developed for the high school level, and suggest some of its implications. This review sheds light on unique and
critical characteristics related to broader integration of bioinformatics in secondary education, which are also relevant to the undergraduate level, and especially on curriculum design, development of suitable learning environments
and teaching and learning processes.
Keywords: bioinformatics education; high school; authenticity; learning environment; domain-specific knowledge; revised
Bloom’s taxonomy
INTRODUCTION
Dramatic progress in biological understanding,
coupled with major advances in experimental techniques, novel approaches and computational analyses,
are transforming the sciences of biology, biotechnology and medicine. Yet, these exciting new fields and
areas of science are rarely integrated into science classrooms or textbooks. This pattern leaves high school
science education lagging behind cutting-edge scientific discoveries, which hold great potential for
supporting students’ understanding and eliciting
their interest and motivation to learn science.
Biology in the 21st century is expanding from a
purely laboratory-based science to an informationaided one [1]. Massive growth in information, due
to experimental and technological advances, has led
to ‘an absolute requirement for computerized databases to store, organize, and index the data and for
specialized tools to view and analyze the data’ [2].
Bioinformatics, an emerging interdisciplinary field,
Corresponding author. Yossy Machluf, Department of Science Teaching, Weizmann Institute of Science, P.O. Box 26, Rehovot
76100, Israel. Tel.: þ972-8-9342273; Fax: þ972-8-9342279; E-mail: [email protected].
Yossy Machluf is a Senior Intern in the Department of Science Teaching, Weizmann Institute of Science. He is a researcher, science
educator and curriculum developer in the fields of biotechnology and bioinformatics.
Anat Yarden is an Associate Professor and head of the Life Sciences Group at the Department of Science Teaching, Weizmann
Institute of Science.
ß The Author 2013. Published by Oxford University Press. For Permissions, please email: [email protected]
Integrating bioinformatics into senior high school
applies principles of computer sciences and information technologies to make the vast, diverse and complex life sciences data more understandable and
useful, and to help realize its full potential [3]. The
ultimate goal of bioinformatics ‘is to enable the discovery of new biological insights as well as to create a
global perspective from which unifying principles in
biology can be discerned’ [2]. Bioinformatics is now
an integral part of modern biology. It has revolutionized and redefined how research is carried out
[2, 4–6] and has had an enormous impact on biotechnology, medicine, agriculture, industry and
related areas.
In light of the ‘information revolution’, the lagging, or limited of bioinformatics educational units
from high school science curricula, is of growing
concern to both the scientific community, which is
eager for bioinformatics-literate individuals who will
pursue careers in the life sciences, and the educational community, which focuses on preparing the
next generation of informed citizens.
In this article, we review recent initiatives to integrate the rapidly growing interdisciplinary field of
bioinformatics into secondary science classrooms.
We discuss insights and lessons from the accumulating experiences in the teaching and learning of bioinformatics in high schools. We present a novel
approach, which we suggest as a uniform and comprehensive platform, to guide the design and characterization of bioinformatics learning materials and
demonstrate its feasibility using our own bioinformatics learning environment. Implications and recommendations for bioinformatics curriculum design,
teacher training and means of improving students’
learning processes are suggested.
BIOINFORMATICS EDUCATIONç
AN OVERVIEW
Despite the tremendous growth in the number of
bioinformatics tools and databases to empower scientific research, only minor increase have been seen
in the number of educational resources [7, 8].
Donovan [9] claimed that ‘given the growing disparity between the rapidly evolving world of research
and an entrenched culture of science education, the
future of science depends on our commitment to
preparing future scientists to work with ‘‘big data’’’.
The origin of bioinformatics education lies in
self-teaching and apprenticeship-like models, where
pioneers in the field taught themselves and each
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other, relying on personal experience and key articles
(e.g. [10]). Today, training programs are being established for bioinformatics services and faculties
[11–16]. The need to prepare 21st-century scientists
has led to a paradigm shift in biology and bioinformatics education [17–23], striving to mirror today’s
research trends and keeping science curricula current.
Initially, efforts were invested in developing structured certificate and degree programs to teach
bioinformatics at the graduate [24–27] and undergraduate [14, 28–32] levels. However, the challenge
of bringing the complex and contemporary science
of bioinformatics to the high school classroom is only
now being addressed (see further on).
A key question is ‘what are the standards of bioinformatics education at each educational level (from
high school to secondary and tertiary levels)?’ The
standards, in turn, should be integrated into policy,
curriculum, instruction and assessment to support
meaningful learning. Standards can be defined in
terms of scientific practices, unifying cross-cutting
concepts, and discipline-related core ideas [33].
Key themes to foster students’ realization of the
real-life contribution of bioinformatics, to promote
their understanding and to increase their interest are
‘integration’ and ‘context’ [18, 23, 29]. The term
‘integration’ means that fundamental concepts and
ideas (or knowledge) as well as competencies (or
practices) of each discipline (biology, computer sciences, mathematics, etc.) should be connected and
integrated, rather than presented as separate discipline-specific units. The term ‘context’ means that the
concepts, ideas and practices should be taught in
relevant scientific contexts, using a problem-based
approach [34–36], rather than as a collection of instructions in a recipe book. Of note, although the
graduate-level programs are mainly designed to teach
the fundamentals of bioinformatics, focusing on
sophisticated computation, mathematics and informatics [27, 29], at the high school level, curricula usually use ‘simple’ bioinformatics as a teaching tool and
provide students with a toolbox of technical skills
and thinking abilities in bioinformatics [37].
Standards and objectives of bioinformatics education
should be consistent with the educational framework
(university versus high school, formal versus nonformal), target population (age, abilities, background,
etc.), time frame (annual topic, short course, etc.)
and resources (technical, educational, materials).
Nevertheless, in all cases, it should strive to develop
a deep sense of the nature of scientific investigation
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and address key actions in bioinformatics-integrated
research (such as data retrieval, analysis, visualization
and modeling) through authentic hands-on and
minds-on activities.
TEACHING AND LEARNING
BIOINFORMATICS IN HIGH
SCHOOL
The need to incorporate bioinformatics into secondary school science classes was first identified by individual teachers and educators who integrated
bioinformatics into their lessons. It is only in recent
years that joint international efforts have been
devoted to teaching bioinformatics in secondary
schools, in the following forms:
educational activities in international societies and
conferences. For example, during the 2010 meeting of the International Society for Computational
Biology Education Committee, a major topic of
discussion was how to get bioinformatics integrated into high school biology classes, organize
a tutorial aimed at secondary school biology and
chemistry teachers interested in learning about
bioinformatics and how to include it in their
curricula and built a collection of usefull resources
to secondary school educators and students looking for information on Bioinformatics teaching
tools (see http://www.iscb.org/high-schoolsecondary-school-resources, and reported in [38]).
an Education section in PLoS computational biology
[39] and special issues in other academic journals
such as Briefings in Bioinformatics [19], provide practical and theoretical information of educational
programs and materials, also for secondary school
educators, teachers and inquisitive minds [40].
and funds for developing bioinformatics learning
materials.
Today, a plethora of bioinformatics-based online
resources, learning modules and outreach programs
(usually at universities, e.g. [41]) are being offered
to high school students (reviewed in [38]), and bioinformatics-based lessons and curricular elements
have been developed [14, 38, 42–53]. Yet, only a
fraction of high school students are exposed to these
materials, partially due to its limited integration in
scientific curricula. Recently, rules were set for the
development [13] and teaching [37, 54] of bioinformatics courses, which can be implied also at the high
school level. As construction of knowledge,
acquisition of skills and motivation are primarily
achieved when students are engaged and persue a
goal [55], it was recommended to develop a series
of inquiry-based research activities that are build on
each other and are linked to preexisting science curricula. Each activity should be simple, in terms of its
objectives, and based on a familiar and relevant biological context. The problem-solving process should
address multiple learning styles, enable the modeling
of the hiden processes and principles of actions of the
bioinformatics tools using paper and pencil.
Moreover, it should allow different rates of progression and provide opportunities for independent
thinking and individualization to increase students’
involvement. In addition, it should allow students
to discover new information and concepts themselves, which in turn should empower students and
serve as a basis for a product of the learning process.
Students’ performance should be assessed and evaluated. The teacher should ensure that students understand the scope and objectives of the activity while
providing appropriate guidance. Teacher should also
ensure ahead of time the availability, compatability,
preparedness and relevance of the bioinformatics
activities and learning materials, the bioinformatics
resources and the computational equipment. Given
the availability of diverse web-based publicly accessible research databases and tools, as well as educational
resources and recommendations, it is now practical,
appropriate and desirable to broadly incorporate bioinformatics into the high school classroom.
Opportunities and challenges
Incorporation of bioinformatics into high school curricula offers great opportunities and major challenges.
Among the main benefits is the applicability of bioinformatics to life sciences curricula and the inherent
features of bioinformatics tools and databases to promote student learning [38, 56]. Bioinformatics naturally fit computer-based scientific inquiry activities
and allow active engagement with big data sets and
current technologies in real-world problem-solving
contexts while using 21st century skills. It may also
enable interactive instruction accompanied by authentic visualizations and modeling, which are in
line with active learning and ‘less traditional’ learning
styles. Moreover, students today are digital ‘natives’,
that is to say they have grown up with computers,
internet and technology, and they therefore possess
natural proficiency and technological competence
[56]. These ‘natives’ have a different approach to
Integrating bioinformatics into senior high school
651
learning, one which is concerned with speed of
access, instant gratification and multitasking abilities.
Obviously, independent of a possible increase in students’ motivation and interest in life sciences research, students can develop a research toolbox,
built up of knowledge skills and thinking approaches
that can serve them as informed citizens and in future
science studies.
Based on the categorization proposed by
Cummings and Temple [56], we map the major
challenges for broader incorporation of bioinformatics in high school education into two interrelated
categories: (i) infrastructure and curriculum and (ii)
the human factor.
knowledge, skills and pedagogy in technology-rich
environments, are infrequent and rare. For some teachers who are not native English speakers, language
is also a barrier. Therefore, many teachers feel less
comfortable with bioinformatics. Teachers who
struggle by themselves to cope with biological context, the complex and dynamic bioinformatics tools
and databases and interpretations of the findings—
also need to support their students, with diverse
learning styles and difficulties and with minimal-tono-teaching assistance. Students are impacted by the
same difficulties as teachers, related to learning to use
bioinformatics resources in diverse research contexts.
Infrastructure and curriculum
Teaching bioinformatics inherently requires computational infrastructure, including, for example, computers, internet access, appropriate bandwidth and
bioinformatics tools, the availability of which is not
trivial. In addition, most high schools do not provide
support policies or the qualified and knowledgeable
personnel required for installation and maintenance
of the hardware and software. In many places, bioinformatics is not integral in the national science curriculum, which implies a lack of standards, of
common and recommended learning materials and
of assessment tools. Teachers often need to develop
their own learning materials or to choose among limited options of learning materials available online,
which are mainly designed for the undergraduate
level. These are usually static and not modular and
cannot be adapted to individual teacher objectives. In
addition, they usually provide neither scaffolding for
learning and instruction nor feedback and reports on
students’ performance. Moreover, the materials are
often outdated and contain broken links, the latter
due to the dynamic nature of the rapidly changing
bioinformatics tools and databases. The authentic bioinformatics resources are also complex and rich in
professional scientific terminology, usually have a
non-user-friendly interface and are not customizable.
These requirements, features and weaknesses pose
difficulties for managers, teachers and students.
Design principles of an authentic bioinformatics learning environment
The human factor
Teachers often lack any prior experience in bioinformatics research or its instruction and have only little
(if any) background in associated disciplines, such as
computation and statistics. Long and continuing professional development programs and short training
courses in bioinformatics, which combine
To successfully implement and broadly incorporate
bioinformatics in high school science, we must recognize, tackle and overcome these challenges. In our
opinion, an essential preliminary step is to determine
a policy that bioinformatics should be integrated as
an elective or obligatory topic in the national science
standards and curriculum. This would necessiate the
definition of practical educational goals, which are
consistent with the target population, the time
frame, the available resources and the national standards. In addtion, minimal technical and computational requirements should be characterized and
provided to schools. Obviously, the rules and recommendations for development of learning materials
and teaching bioinformatics, as described before,
should be implemented. Support, to both students
and teachers, is another key issue. The learning materials should encompasses diverse scaffolding means
and real-time feedback to support students’ knowledge construction, at different grades following the
spiral learning model. Short- and long-term training
programs as well as a continuous support for teachers
should be offered. Moreover, an assessment tool,
which is consistent with the learning processes,
should be designed. Above all, considering the challenges and oppertunities, one should ensure collaboration and communication between policy makers,
inspectors, developers, scientists, science educators
and teachers—along all stages of design, development, enactment, evaluation and refinement.
To illustrate means of approaching some of the
aforementioned challenges, we describe the rationale, guidelines and design principles underlying the
development of a web-based learning environment
[52] that is aimed at introducing bioinformatics into a
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high school biotechnology majors curriculum (60 h,
12th grade) in Israel (for additional information, see
Machluf and Yarden [57]). The curriculum for biotechnology majors includes obligatory topics such as
genetic engineering and biochemistry, and the elective topics of immunodiagnostics and immunotherapy, tissue culture, environmental biotechnology,
bio-nanotechnology and advanced laboratories, as
well as bioinformatics [58]. It has been recently
(2011–12 academic year) introduced into the national matriculation examination in Biotechnology
in Israel as an innovative online problem-solving
type assessment comprising 12% of the total
grade. Noteworthy, the level of the 12th-grade
senior high school biology curriculum is in a way
similar to the advanced placement biology in the
United States. Therefore, we believe that the following description, analysis and implication are relevant
to bioinformatics curriculum designers, science educators and teachers at both high school and undergraduate levels.
In the learning environment (Figure 1), both
pedagogy and technology were recruited for
first-hand active learning processes and educational
purposes aimed at engaging students in scientifically
authentic inquiry-based activities in biotechnology,
approaching real-world problems, using diverse bioinformatics tools and databases, while acquiring and
applying modern scientific practices (skills, knowledge and mode of thinking). The learning environment was designed with the canonical perspective on
authentic science education in mind (following
Buxton [59]), namely, practices that resemble authentic scientific research, as they are carried out
by the scientific community. Authentic practices
can offer students opportunities to develop a contextualized and deep understanding of scientific knowledge and of how this knowledge is acquired,
evaluated and developed [60–62], as well as to
invoke the reasoning that scientists use and the
epistemology underlying authentic inquiry [63].
The activities in the learning environment were
developed based on primary research articles, which
were tailored and adapted to high school cognitive
level and knowledge, and were selected according to
(i) the relevance of the scientific context to students’
Figure 1: The learning environment’s home page. The various units are presented, as well as the scientifically
authentic inquiry activities and the bioinformatics tools.
Integrating bioinformatics into senior high school
interests; (ii) a clear biotechnological application;
(iii) use of a variety of bioinformatics tools and databases that are suitable for the high school students’
cognitive level; (iv) leading-edge high-impact subjects that are broadly covered in the popular scientific
literature and in the public media, indicating scientific
importance and accessibility; (v) clear connections to
principles and techniques in the biotechnology syllabus; and (vi) representation of diverse organisms and
different molecules (DNA, RNA and proteins). The
topics of the activities focus on authentic investigations that are aimed at improving humans’ life quality
and expectancy: (i) identifying alleles of hemoglobin
conferring resistance to malaria; (ii) screening for
novel genes involved in antibiotic biosynthesis; (iii)
exploring the genotype–phenotype relations in
cystic fibrosis; (iv) searching for a competitive inhibitor of the anthrax toxin; (v) characterizing the sequence and 3D structure of green fluorescent
protein. More details on the activities, the research
objectives and rationale, questions addressed and
choice of tools can be found in Supplementary
Materials (Supplementary Appendix 1).
In three activities (termed ‘in-depth activities’, i–iii
above), the students become familiar with bioinformatics tools and databases for the first time, and therefore emphasis is placed on prompting understanding
via hand-in-hand guidance through each step of the
inquiry process, mainly focusing on procedures and
concepts. The remaining two activities (termed
‘integrated activities’, iv and v above) are based on
this previous experience, hence highlighting the
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research strategy, considerations of selecting bioinformatics tools and their contribution to basic and
applied scientific research. Students use most tools
once in an ‘in-depth activity’ and once in an
‘integrated activity’ (Table 1). Though activities are
modular, the ‘integrated activities’ are connected to
and build on the experience acquired in the ‘in-depth
activities’.
Each multistep activity begins with a detailed
background for the scientific investigation, including
images and external links and animations, presenting
the rationale, goal, design and 2–4 key tasks of the
investigation. Throughout the inquiry process,
which is embedded within a large number of questions and assignments, the students experience different scientific practices; they are required to
coordinate between different types of knowledge
from different scientific disciplines, to recall prior
content knowledge, to apply technical skills in
using bioinformatics tools, to reason scientifically,
to make decisions following a strategic plan and to
evaluate and justify the scientific process and its steps.
The selected bioinformatics tools (Entrez, Blast-N,
Blast-P, ClustalW, ORF Finder, Primer3Plus,
Prosite and Jmol) are basic yet fundamental;
namely, they are well-supported tools with decent
interfaces, which are not difficult for teachers and
students to use; they are widely used by scientists
and enable acquisition of central bioinformatics principles and approaches. Moreover, the tools are freely
available on the web, and the databases are
frequently updated, both reflecting key practices of
Table 1: Inquiry-based activities and bioinformatics tools in the learning environment ‘Bioinformatics in the Service
of Biotechnology’ at http://stwww.weizmann.ac.il/g-bio/bioinfo
Bioinformatics
tools
Activities
‘Integrated activities’
Identifying alleles
of hemoglobin
conferring
resistance
to malaria
Entrez
Blast-N
Blast-P
ClustalW
Primer3þ
ORF Finder
Prosite
Jmol
‘In-depth activities’
Screening for
novel genes
involved in
antibiotic
biosynthesis
Exploring the
genotype^phenotype
relations in
cystic fibrosis
&
X
Characterizing
the sequence and
3D structure of
green fluorescent
protein
Searching for a
competitive
inhibitor of the
anthrax toxin
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
&
X
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Machluf and Yarden
the scientific community, such as sharing resources,
and the dynamic nature of scientific knowledge. The
tools are introduced to the learners in a virtual
‘Bioinformatics Toolbox’ that includes detailed
interactive tutorials and written texts. Although the
algorithms are not demonstrated, their principles of
operation are discussed.
An introductory unit lays the groundwork for
learning, comprising subject matter knowledge in
biology, biotechnology and bioinformatics. It covers
basic concepts and core ideas in biology such as the
central dogma, from a DNA sequence to protein
function, and regulation of gene expression at all
levels. The bioinformatics field is presented from historical and research perspectives. Its contribution is
illustrated by the paradigm shift in evolutionary research and modes of integration in modern basic and
applied biotechnological research. More details on the
introductory unit can be found in the Supplementary
Materials (Supplementary Appendix 2).
Scaffolding is provided by automatic reflections on
students’ answers to multiple-choice questions
(offering corrections, explanations and empowerment), textual descriptions and graphical annotations
to illuminate bioinformatics tools’ interfaces and
result pages and reference to a scientific dictionary.
To make the scientific thinking visible (and epistemologically transparent), a summary of each investigation, including the use and contribution of each
bioinformatics tool to each task, appears at the beginning and end of each activity.
An assessment unit includes short exercises and
matriculation exam-like questions to provide students with a deeper understanding of the bioinformatics approach and to improve their skills in
bioinformatics practices. Documentation of curricular requirements of bioinformatics mastery is essential
to direct instruction and learning.
Altogether, the bioinformatics learning environment meets the challenges [56] and fulfills the guidelines [13, 37] for bioinformatics education, to enable
high school students to acquire a scientific toolbox
containing bioinformatics-specific knowledge and
skills, as well as general research practices. These are
important components of scientific literacy for both
informed citizens and future life science researchers.
Teachers’ perspectiveçtraining and
support
To support the implementation of bioinformatics in
the biotechnology syllabus, teachers were recruited
as agents of change. To this end, outstanding senior
teachers, with either a MSc or a PhD degree in
biology, were involved in the design of the learning
environment, in the development of learning materials, teachers’ guides, instructional means and assessment tools and in other teachers’ preparation
and support. This was achieved by a 1-year long
teachers’ professional development program in bioinformatics within the framework of RothschildWeizmann Program for Excellence in Science
Education, which is now running for the 3rd
year. The program is aimed at establishing a community of teachers who desire to be innovative, and
collaborate in enhancing the implementation of
bioinformatics into high schools [64]. Moreover,
training courses (56 h) and learning and teaching
materials design workshops (28 h) for teachers are
offered on a nationwide scale, together with monitoring, supervision and constant guidance at the
personal level. The close collaboration between
the teachers and developers and researchers contributed to linking bioinformatics to preexisting biotechnology curricula, to setting realistic and
practical expectations from students and teachers
that match the syllabus’s scope, to teachers’ sense
of ownership of the learning environment and to
developing their identity as reform-minded science
teachers. These actions have led to the establishment of a community of teachers, developers and
researchers who collaborate in adapting the new
learning environment and promoting its implementation and distribution.
A teachers’ guide is inherent to the learning environment. Suggestions for instruction, enactment
and evaluation are provided for each activity, as
well as answers to the questions, a closed forum for
teachers, presentations and instructional materials. A
teachers’ interface for analysis of students’ performance, as answers to questions that are embedded in
the learning environment and stored online in a
database, is also integrated into the learning environment. Examples and more details on the teachers’
guide can be found in the Supplementary Materials
(Supplementary Appendix 3).
Research and lessons
Endeavors to incorporate bioinformatics into high
school science classrooms are only seldom accompanied by educational research at the interface of bioinformatics curriculum design, teaching and learning
processes. Bioinformatics is a complex field in nature,
Integrating bioinformatics into senior high school
necessitating wide procedural skills to use tools and
databases coupled with factual knowledge and strategic thinking.
A seminal case study by Wefer and Anderson
[65] highlighted the individual and marked differences in the way students contextualize and process
domain-specific knowledge and skills associated
with a bioinformatics unit. Their analysis was
based on four components: specific knowledge and
facts (concrete factual knowledge), higher-order
knowledge (principles, theories and generalizations
related to bioinformatics that draw holistically from
declarative and procedural knowledge), procedural
skills (skills needed to use bioinformatics programs)
and analytical thinking skills (skills needed to
apply factual and procedural knowledge to interpret
and apply bioinformatics information in various
situations). In this view, bioinformatics mastery
requires integration of factual information with
procedural knowledge and analytical skills in a
well-rationalized and coherent way. Accordingly,
recommendations were made for teachers to
design lessons in a way that ‘helps students to comprehensively integrate these cognitive dimensions in
a holistic fashion’ [65].
Another aspect of integration was also demonstrated recently when a few high school students
who experienced a computational biology course
persisted in thinking of separate and irrelevant
‘computer’ and ‘biology’ units, rather than seeing
the connections between them [49]. Similar findings were observed at the undergraduate level,
where students were found to differ in their ability
to understand and articulate the biological significance of the bioinformatics results, as well as to
understand the differences between listing a fact,
carrying out a procedure or running a computer
program and drawing inference and insight from
them [66]. Buttigieg [67] claimed that to grant
the audience perspective on ‘why and how’ bioinformatics research is carried out, one should develop the factual knowledge of biology alongside
the procedural knowledge of computer science
and mathematics in a cohesive manner.
We previously developed a research simulation in
genetics and bioinformatics for high school biology
majors [51] and used it to characterize the teaching
approaches and to examine how learning through
the environment influences students’ acquisition
of genetics knowledge and their comprehension
of scientific practices [68–70]. We found that
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engagement in an authentic scientific research simulation requires continuous application of facts and
procedures while reasoning scientifically and
making decisions. Thus, the ability to coordinate
and use different knowledge dimensions, mainly
conditional knowledge (following [71]), were
shown to be at the heart of performing authentic
scientific research. Teachers were shown to play a
key role in supporting the learning of bioinformatics
and in promoting students’ use of conditional
knowledge in a manner similar to scientists in the
course of performing authentic research [70]. This
study was based on the definitions proposed by
Alexander and Judy [71] of declarative knowledge
(knowing ‘what’—factual knowledge), procedural
knowledge (knowing ‘how’—compilation of declarative knowledge into functional units that
incorporate domain-specific strategies) and conditional knowledge (knowing ‘when and where’ to
access certain facts or use particular procedures).
We [68, 69] and others [32, 72] found that learning
bioinformatics can complement and enhance understanding of biological content, such as genetics.
Interestingly, at both the high school and university
levels, two types of learners—research-oriented and
task-oriented—were identified on the basis of the
differences in the ways they seized opportunities to
recognize the research practices, which in turn
influenced their learning outcomes [66, 69].
In addition to the benefits and challenges involved
in the incorporation of a modern interdisciplinary
field into the high school classroom, this literature
survey brings to light the disparity in theoretical perspectives and terminologies related to knowledge
and skills. Clearly, different terms are used to refer
to similar types of knowledge, and similar terms are
used to refer to different types of knowledge. For
example, what Wefer and Anderson [65] referred
to as ‘analytical thinking skills’, others refer to as
‘conditional knowledge’ [71] or ‘strategic knowledge’ [73]. Yet strategic knowledge was also considered a special form of procedural knowledge [71].
We need a uniform comprehensive platform to
guide the design of bioinformatics curricula, to
enable the characterization of learning materials
(see further on), to analyze students’ learning styles,
outcomes and needs, to portray teaching strategies
and means, to draw recommendations on curriculum
design, teaching and learning processes and to promote bioinformatics mastery among secondary
school students.
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TYPES OF DOMAIN-KNOWLEDGE
AND COGNITIVE PROCESSES
INVOLVED IN BIOINFORMATICS
COMPETENCY
The bioinformatics field is rich in a wide range of
domain-specific knowledge and skills, which originate from different disciplines, as well as in general
scientific practices and cognitive processes. These
parameters are usually required within a school bioinformatics curriculum, as students study using a bioinformatics activity, and are evaluated by questions
embedded within the bioinformatics resources. We
suggest a set of criteria to gain a comprehensive view
of the characteristics of the questions embedded in
bioinformatics learning materials. Such a characterization enables performing a quantitative analysis of
students’ learning outcomes and can serve as a basis
to describe the teaching approaches involved. A unified platform, which is based on knowledge, cognition and scientific approach, can serve for the analysis
of curriculum design and content, as well as learning
and teaching processes, outcomes and personal attitudes (see later in the text). The findings and insights
may lead to the construction of operational recommendations for policy makers, developers of learning
and teaching materials, teachers–trainers and teachers, which in turn may enable to improve and
expand the educational resources, their proper use,
and broader integration into high schools. This general platform can be supplemented with specific features of each bioinformatics learning module/course,
such as the software tools and databases, the topics of
bioinformatics activities, module design and format
and so forth. The proposed criteria are as follows.
Types of knowledge
Frequent attempts have been made to construct a
theoretical framework for knowledge classification,
and various types of knowledge have been termed.
This criterion is based on a view of scientific knowledge as consisting of four distinguishable but related
elements [74]:
methods and appropriate usage and experimental
design [76], as well as perceptual motor skills [75].
This knowledge was also termed ‘concepts of evidence’ [77] or ‘thinking behind the doing’ [78].
Situational knowledge—knowledge of situations
that enable the solver to sift relevant features out
of the problem statement and to supplement information in the statement [74].
Strategic knowledge—a general plan of action for
the problem-solving process [74] or knowing the
conditions ‘when and where’ knowledge would
be applicable [71, 79]. These are domain-specific
heuristics that aid in the regulation, execution and
evaluation of a task [71, 73].
This platform fits the characteristics of bioinformatics research. For instance, when a research question or objective is defined, the researcher uses
heuristics and designs a strategy to follow them to
get closer to a potential solution. Accordingly, the
researcher selects appropriate experimental techniques and bioinformatics tools, considering both
the current knowledge base of facts, concepts and
theories and the mode of action, demands and application of each bioinformatics tool (and database).
Then the researcher uses bioinformatics tools while
making decisions on both the diverse options of
using each tool and the interpretation and making
sense of the results. This is a multistep, iterative and
reflective process.
In the bioinformatics learning environment, declarative knowledge is mainly presented in the introductory unit (general concepts and models in
biology, bioinformatics and biotechnology), and in
the dictionary, procedural knowledge is mainly displayed in the tutorials (specific to each bioinformatics
tool), whereas the activities and exercises require the
construction, application and integration of these
two types of knowledge along with situational
knowledge and strategic knowledge.
Scientific approach
Declarative knowledge—knowledge of ‘what’
facts, concepts, laws, principles and theories are
[74]. This knowledge is also known as conceptual,
propositional [75], substantive or content
knowledge.
Procedural knowledge—knowing ‘how’ to perform valid actions in certain processes or routines.
It also includes an understanding of techniques,
The scientific approach or discipline from which the
knowledge stems. We distinguish between questions
that require the use of either biological topic/context-associated knowledge or bioinformatics-related
knowledge and skills or a combination of both.
When higher resolution is required, for instance
when computational programming and statistical
analysis are integral components of the activity, one
Integrating bioinformatics into senior high school
might add additional categories, e.g. computation/
programming and statistics, respectively.
Cognitive domain
Classifications of cognitive demand schemes are largely based on categorizations of knowledge types
and associated mental processes that are used to
describe educational objectives or assessment tasks.
We suggest following the well-known revised
Bloom’s Taxonomy [80], which identifies six hierarchical categories of cognitive process dimensions:
Remember, Understand, Apply, Analyze, Evaluate
and Create.
Analogous to this taxonomy for learning, and
despite some criticism, Jungck suggested a taxonomy for ‘quantitative reasoning in biology’,
namely, an ‘implementable sequence of steps that
is intended to develop students’ metacognitive
growth in mathematical thinking through explicit
activities’ [81].
CHARACTERISTICS OF THE
BIOINFORMATICS LEARNING
ENVIRONMENT
In the ‘Bioinformatics in the Service of
Biotechnology’ learning environment, declarative
knowledge in biology and bioinformatics is mainly
provided in the ‘Introductory’ and ‘Dictionary’ units.
The ‘Tool-Box’ deals mainly with procedural aspects
of operating bioinformatics tools and to a lesser
extent with declarative concepts of their operation,
as well as scientific strategies or conditions for using
them. In the ‘Activities’ and ‘Questions’ units, bioinformatics tools are used in biological contexts in
problem-solving approaches, where strategic knowledge and situational knowledge are required.
To examine the feasibility of the proposed set of
criteria, the questions embedded in two activities (1
and 2 above, n ¼ 63 questions) from the learning
environment were characterized. We also noted
the type of question, distinguishing between openended and multiple-choice. Importantly, although
many questions required a combination of two
(or more) types of knowledge, questions were classified based on the predominant type of knowledge
(examples of questions’ classification are provided
in the Supplementary Materials—Supplementary
Appendix 4).
The distribution of the questions in those two
activities was in accordance with the goal of
657
introducing students to the bioinformatics approach
and the procedures for use of bioinformatics tools.
Providing answers to approximately half of the questions in these ‘in-depth activities’ requires the use of
procedural knowledge, whereas questions that
require the use of either declarative or situational
knowledge are almost equally represented, and
those that require the use of strategic knowledge are
the least common (Table 2). Similarly, most questions
deal with the bioinformatics approach, solely or in
combination with a biological approach. Logically,
most questions are associated with the cognitive processes ‘Understand’ and ‘Apply’ for the newly
acquired knowledge. Higher-order thinking questions are also represented, yet to a lesser extent.
Multiple-choice questions are overrepresented with
respect to open-ended questions, probably because
they allow automated feedback to students’ answers.
Interestingly, providing answers to most multiplechoice questions necessitates the use of procedural
knowledge, which mainly stems from the bioinformatics approach and is associated with the cognitive
process of ‘Analyze’. On the other hand, providing
answers to most open-ended questions necessitates
the use of declarative knowledge, which mainly
stems from the biological approach and is associated
with the cognitive process ‘Understand’ (data not
shown).
Table 2: Classification of questions embedded in two
activities ‘identifying alleles of hemoglobin conferring
resistance to malaria’ and ‘screening for novel genes
involved in antibiotic biosynthesis’ (n ¼ 63)
Classification
Categories
Number of
questionsa
Significanceb
Type of question
Multiple choice
Open ended
40 (63.5%)
23 (36.5%)
P < 0.05
Scientific
approach
Biological approach
Bioinformatics approach
Combined approach
11 (17.5%)
36 (57.1%)
16 (25.4%)
P < 0.01
Domain-specific
knowledge
Declarative knowledge
Procedural knowledge
Situational knowledge
Strategic knowledge
14 (22.2%)
32 (50.8%)
12 (19.0%)
5 (7.9%)
P < 0.001
Revised Bloom’s
taxonomy of
cognitive
processes
Remember
Understand
Apply
Analyze
Evaluate
Create
3 (4.8%)
25 (39.7%)
18 (28.6%)
10 (15.9%)
3 (4.8%)
4 (6.3%)
P < 0.001
a
The actual number (left) and percentage (right, in parentheses) of
questions in each classification category. bChi-square test was applied.
Significance implies that there is a difference between the expected
and observed frequency of at least one of the question categories.
658
Machluf and Yarden
IMPLICATIONS FOR CURRICULUM
DESIGN,TEACHERS’ TRAINING
AND LEARNING PROCESSES
Such characterization of learning materials may also
be used to analyze students’ performance (by the answers they provide to these questions) and attitudes
toward bioinformatics (by questionnaires and interviews), e.g. which practices and types of knowledge
they perceive as harder to deal with or requiring more
support and so forth. Likewise, teachings strategies
and teachers’ beliefs on the incorporation of bioinformatics into the high school classroom can also be
analyzed with reference to these criteria.
Continuous coordination between different types
of knowledge and sources of information is among
the characteristics that differentiate real authentic scientific inquiry from tasks commonly used in schools
[63]. The learning environment ‘Bioinformatics in
the Service of Biotechnology’, its activities and the
questions embedded in it comprehensively integrate
and present unique features of modern authentic
bioinformatics-combined scientific research, which
is rich in diverse procedural skills coupled with the
declarative knowledge and strategic thinking
required to understand and master bioinformatics
approaches and applications.
The analysis proposed here for the bioinformatics
learning environment may shed light on the means by
which high school students perceive and deal with
scientifically authentic inquiry activities, as well as
on the means used for instruction of such materials.
Attempts to make science learning better resemble
authentic scientific practices have led to educational
reforms, at least since Dewey [82]. Nevertheless, only
a few educational researchers have adopted authentic
scientific practices, as they are practiced by the scientific community, as a basis for examining the teaching
and learning of science (e.g. [83, 84]). We envision
that this framework for analyzing curriculum design
and content, as well as learning and teaching processes, might be valuable to foster bioinformatics education in high schools (and universities). For instance,
it might uncover the kinds of questions students (and
teachers) struggle with, and the derived recommendations for adequate instruction may be integrated
into the learning environment as well as the teachers’
training courses. It can also serve as a monitoring tool
for quality-control processes for developers and policy makers to ensure that the bioinformatics resource
characteristics are in line with their educational and
scientific goals.
SUPPLEMENTARY DATA
Supplementary data are available online at http://
bib.oxfordjournals.org/.
Key Points
The evolution of bioinformatics education should keep up with
advances in bioinformatics research.
Given the availability of publicly accessible research databases
and tools, as well as educational resources, it is now practical,
appropriate and desirable to broadly incorporate bioinformatics
into the high school classroom.
Bioinformatics resources for high school students should be
designed and developed to make the most of educational opportunities and to overcome the challenges involved.
Endeavors to incorporate bioinformatics into high school science
classrooms should be accompanied by educational research at
the interface of bioinformatics curriculum design, teaching and
learning processes.
Characterizing the types of knowledge, the scientific approach
and the cognitive domain required to answer questions
embedded in bioinformatics learning environments is proposed
as a platform for analysis of students’ learning outcomes.
Acknowledgements
We wish to thank Hadas Gelbart and Shifra Ben-Dor for fruitful
discussions; Orna Dahan, Amir Mitchell, Carmit AvidanShpalter, and Hadas Gelbart for collaborative efforts to design
and develop the bioinformatics curriculum, and Eilat Avraham,
the national supervisor for biotechnology teaching at the
Ministry of Education, who had the vision and enterprise
to lead the way in bringing bioinformatics to high-school
classrooms.
FUNDING
The development of the bioinformatics learning
environment and training courses were funded by
the Ministry of Education and The Israeli Science
Teaching Center Grant. Teachers’ professional
development program, within the framework of
the Rothschild-Weizmann Program for Excellence
in Science Education, was generously supported by
Caesaria Foundation.
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