Integrating Science and Technology: Using TechnologicalPedagogical Content Knowledge as a Framework to Studythe Practices of Science Teachers

Rose M. Pringle • Kara Dawson • Albert D. Ritzhaupt

Published online: 13 March 2015

� Springer Science+Business Media New York 2015

Abstract In this study, we examined how teachers in-

volved in a yearlong technology integration initiative

planned to enact technological, pedagogical, and content

practices in science lessons. These science teachers, en-

gaged in an initiative to integrate educational technology in

inquiry-based science lessons, provided a total of 525 les-

son plans for this study. While our findings indicated an

increase in technology-related practices, including the use

of sophisticated hardware, very little improvements oc-

curred with fostering inquiry-based science and effective

science-specific pedagogy. In addition, our conceptual

framework, technological pedagogical content knowledge,

as a lens to examine teachers’ intentions as documented in

their lesson plans, provided an additional platform from

which to investigate technology integration practices

within the ambit of reform science teaching practices. This

study, therefore, contributes knowledge about the structure

and agenda of professional development initiatives that

involve educational technology and integration into content

knowledge disciplines such as science.

Keywords Integrating science and technology �Technological pedagogical content knowledge � Sciencelesson plans

Introduction

The National Education Technology Plan 2010 (NETP)

developed by the United States Department of Education’s

Office of Educational Technology signals a strong com-

mitment to the integration of technology in all levels of the

educational system. This plan recognizes the integral role

of technology in every aspect of daily lives and as such

calls for educators to leverage technology-based learning in

order to ensure that students are provided with authentic,

engaging, and meaningful learning experiences (NETP

2010). Likewise, other science educational reform docu-

ments [e.g., American Association for the Advancement of

Science (AAAS) 1989; 1993; and National Research

Council (NRC) 1996] have recommended the use of

technology to promote students’ participation in learning

experiences that allow them to adopt the attitudes and

dispositions typical of scientists (McNeill and Pimentel

2010; Slykhuis and Krall 2011). In response to these

mandates, science educators and school leaders have re-

newed their efforts to promote the integration of learning

technologies and inquiry-based practices into their in-

struction in order to improve students’ understanding of

science and also to better prepare them for the twenty-first

century workforce. Technologies, from probes to comput-

ers and digital whiteboards to smartphones, have the po-

tential to enhance students’ understanding of natural

phenomena (Hug et al. 2005; NRC National 1996) and to

successfully engage them in the learning process (Blu-

menfeld et al. 2000). With increased accessibility to tech-

nologies, more science teachers have begun to embrace

their use as essential for illustrating and reinforcing science

concepts, promoting student learning, and enhancing

problem solving and data analysis (Guzey and Roehrig

2009; Slykhuis and Krall 2011).

R. M. Pringle � K. Dawson � A. D. Ritzhaupt (&)

School of Teaching and Learning, College of Education,

University of Florida, 2423 Norman Hall,

PO Box 117048, Gainesville, FL 32611, USA

e-mail: aritzhaupt@gmail.com

123

J Sci Educ Technol (2015) 24:648–662

DOI 10.1007/s10956-015-9553-9

Context

Since 2002, state education agencies have awarded mil-

lions of dollars in Enhancing Education through Tech-

nology (EETT) funding to support technology-rich

classroom environments and professional development

experiences that increase effective technology integration

practices and student learning across the USA [State

Educational Technology Directors Association (SETDA)

2011]. This study is situated within one such statewide

initiative in Florida designed to accomplish the following

goals: (1) improve the technology integration practices of

math and science teachers, (2) increase access to techno-

logical tools and infrastructure, (3) strengthen teacher and

administrator ICT skills, (4) strength student ICT skills,

and (5) improve student achievement (Dawson et al. 2012).

This particular study is focused on the technology inte-

gration practices of science teachers (i.e., Goal 1) par-

ticipating in this yearlong initiative.

The technology integration initiative involved 28 funded

projects within 24 school districts. These districts represent

the diversity of the state with a mix of urban and rural

districts. Student numbers in these districts vary from ap-

proximately 1000 students in the district to nearly 200,000

students. Likewise, teacher population varies from less

than 100 teachers to more than 13,000. Economic condi-

tions in the districts also vary, with the number of students

on free or reduced lunches ranging from 36 to 100 %, the

number of students living in poverty ranging from 10 to

29 %, and the unemployment rates ranging from 8 to 16 %.

During the initiative, teachers were engaged in a four-

day statewide professional development program. This

professional development provided a forum for educators

to collaborate and engage in learning experiences for

themselves and their students, using digital tools. Teachers

funded through this initiative as well as teachers from non-

funded districts participated in the professional develop-

ment program. The program was led by educational tech-

nology specialists and focused on technologies that could

be used across content areas such as digital audio, digital

video, and presentation tools. It was neither focused on

science nor led by science educators.

This statewide professional development was comple-

mented by local efforts throughout the grant period. These

localized activities allowed individual school districts to

make decisions regarding professional development based

on their own needs, but the mechanisms by which districts

reported this professional development make it impossible

to richly describe the professional development within or

across projects. Required self-reports from district leaders

suggest that exemplary professional development features

such as access to support and resources, opportunities for

collaboration with peers, and opportunities to plan for

technology use within the context of science content

knowledge were present in many of the local professional

development efforts (Dawson et al. 2012).

Research Questions

Our study contributes to the literature base by examining

the way science teachers participating in a yearlong tech-

nology integration initiative used technology in their sci-

ence lesson plans. While these uses cannot be directly

linked to particular components of the initiative such as

professional development or the acquisition of particular

technology tools, understanding how teachers use tech-

nology is important in and of itself (Lei 2007; Darling-

Hammond 2000). Specifically, the following research

questions guided the study:

1. In what ways do science teachers involved in a

yearlong technology integration initiative enact tech-

nological, pedagogical and content practices in

lessons?

2. In what ways, if any, do these practices change during

a yearlong technology integration initiative?

Conceptual Framework

Technological pedagogical content knowledge (TPACK)

was used to frame this study and capture insights into

science teachers’ practices with technology. TPACK was

selected because it organizes the types of knowledge

needed in order to integrate technology in K-12 teaching

and learning based on technology, pedagogy, and content

knowledge (Mishra and Koehler 2006). TPACK builds on

pedagogical content knowledge (PCK) literature first pro-

posed by Shulman (1986). Shulman conceptualized PCK as

specialized knowledge distinguishing the teacher from the

content specialist and included, ‘‘an understanding of how

particular topics, problems, or issues are organized, pre-

sented, and adapted to the diverse interests and abilities of

learners, and presented for instruction’’ (Shulman 1986,

p. 8). While PCK has two primary components—pedagogy

and content—TPACK adds a third component—tech-

nology. Within the TPACK framework are a total of seven

constructs visually represented in the three-circle Venn

diagram shown in Fig. 1.

The three major constructs include the following: (1)

technological knowledge (TK) which refers to knowledge

about technologies for use in teaching and learning; (2)

pedagogical knowledge (PK) which refers to the processes

and methods of teaching and learning; and (3) content

knowledge (CK) which refers to the subject area

J Sci Educ Technol (2015) 24:648–662 649

123

understandings. These three major constructs intersect to

form three additional constructs: (4) technological peda-

gogical knowledge (TPK); (5) pedagogical content

knowledge (PCK); and (6) technological content knowl-

edge (TCK). Each construct refers to the merger of two

types of knowledge. For example, technological pedago-

gical content knowledge refers to uniting knowledge

of teaching and learning pedagogy with knowledge of

technology. TPACK lies within the center triadic inter-

section and represents a merger of all three types of

knowledge.

Previously, TPACK has been used as a framework to

support research on technology integration including case

studies of mathematics teachers involved in a learner-cen-

tered professional development project (Polly 2011) and

mathematics and science preservice teachers enrolled in

methods courses (Neiss 2005); survey research to ascertain

K-12 online teachers perceptions of their TPACK knowl-

edge (Archambault and Crippen 2009); studying TPACK

development in faculty and students in a learning technology

by design seminar (Koehler and Mishra 2005); interpretive

research examining growth of TPACK knowledge exhibited

by inservice teachers enrolled in an online graduate course

(Niess et al. 2010); and design-based research to support

TPACK development in preservice teachers (Mishra and

Koehler 2006). In each case, TPACK constructs were de-

fined within the context of the study.

However, some have questioned the practicality of

measuring TPACK as a multi-dimensional construct (Ar-

chambault and Barnett 2010; Brantley-Dias and Ertmer

2013). For instance, Brantley-Dias and Ertmer (2013)

criticize the TPACK framework for not clearly gauging

what types of pedagogy or curricula provide a ‘‘best fit’’ for

technology integration. Further, Archambault and Barnett

(2010) call into question the theoretical foundations of

TPACK by stating that Shulman’s PCK operated with

difficult to define domains that make the overall construct

unclear. Brantley-Dias and Ertmer (2013) state that

TPACK possesses a critical flaw of being both too large

(seven distinct knowledge types) and too small (compart-

mentalized) for practical use or measure.

In this study, the TPACK constructs were defined using

literature from teaching and learning, science education,

and educational technology. For example, technological

content knowledge (TCK), or the merger of technology and

content knowledge, was represented by the types of sci-

ence-specific technologies teachers used in their lesson

plans, and the pedagogical content knowledge was repre-

sented by evidence of inquiry-based science teaching

(Michaels et al. 2008). These definitions are further de-

scribed later in the paper.

Method

Study Design

There is a precedent for using lesson plans and other class-

room artifacts as proxies for teacher practices (Darling-

Hammond 2010; Jacobs et al. 2008; Silk et al. 2009; Silver

et al. 2009). Examining lesson plans can provide insight into

teachers’ approaches to science teaching and learning.

Furthermore, lesson plans ‘‘allow for evaluation of longer

‘chunks’ of planned instruction, allowing insight into the

teachers’ decisions about sequence of and relationships be-

tween activities and topics as well as their assessment

strategies, neither of which are commonly evident when

observing a single class period’’ (Jacobs et al. 2008, p. 1098).

Lesson plans provide a better idea, compared to a snapshot

observation of the enacted curriculum, of teachers’ beliefs

about teaching science with technology and reflect how

teachers envision the integration of their preferred tech-

nology into contemporary science teaching practices

(Brown 1998). In this study, we used lesson plans as proxies

for teacher practice. We embraced the process of lesson

planning as a crucial component of teachers’ practices.

The TPACK framework provided us with a way to or-

ganize the types of knowledge needed in order to integrate

technology in science teaching and learning. It also al-

lowed us to develop coding criteria for the lesson plans.

While the TPACK framework is inherently complex and

contextually bound (Mishra and Koehler 2006), this study

separated the components in order to explore science and

technology integration practices in a way that is consistent

Fig. 1 Technological pedagogical content knowledge framework

650 J Sci Educ Technol (2015) 24:648–662

123

and reliable across multiple lesson plans and multiple re-

viewers. We recognized that knowledge and practice are

related but not synonymous. While we used a knowledge

framework (i.e., TPACK) to guide our study of teacher

practice, we understood that in many cases, we were cod-

ing information about practice that might not represent the

complex nature of teacher knowledge.

We also recognized our results were limited by the in-

formation on which we chose to focus and on the quality

and level of detail provided in the lessons plans. We ad-

dressed these limitations in several ways. First, we defined

our criteria based on literature in science education and

educational technology. Second, our research team in-

cluded both science educators and educational tech-

nologists. Third, we conducted extensive reviewer training

and inter-rater agreement work. Finally, we provided an

online template to collect consistent information from the

teachers and the review process from the reviewers.

Sample

Participating science teachers were asked to submit their

best science lesson using technology at the beginning of the

technology integration initiative and then again at the end.

Teachers submitted their lessons through an online system

that required information such as lesson title, grade level,

content area, estimated time, objectives/standards, proce-

dures, and assessments (see Fig. 2). All submissions were

time stamped to determine whether they were submitted at

the beginning or end of the initiative. The system was

closed in the middle of the initiative to easily identify pre-

and post-submissions. Each lesson plan was reviewed for

completeness and to ensure a science focus. The research

team analyzed a total of 525 lesson plans. Of the 525 lesson

plans, 306 were pre-lessons and 219 were post-lessons.

Coding Criteria

Teacher practices were identified using literature-based

indicators related to six constructs identified in the TPACK

framework and described earlier. Table 1 overviews these

literature-based indicators and each TPACK component.

Technological Knowledge

TK was represented by the general software and hardware

used in the lesson plans. Lists of possible software (see

Table 2) and hardware (see Table 3) were modified from two

valid and reliable instruments used in previous studies of

technology use (Hogarty et al. 2003; Lowther andRoss 2001).

Pedagogical Knowledge

PK was represented by the attributes of meaningful learn-

ing as defined by (Jonassen et al. 2003) and identified in the

Fig. 2 Lesson plan submission

tool

J Sci Educ Technol (2015) 24:648–662 651

123

lesson plans. Specifically, reviewers looked for evidence of

four attributes of meaningful learning: (a) active; evidence

of students developing knowledge and skills by interacting

with their environment (i.e., manipulating objects, ob-

serving phenomena, debating, and role-playing), (b) con-

structive; students representing their learning in the

creation of artifacts, (c) authentic; learning situated in a

meaningful real-world context, and (d) cooperative; stu-

dents engage in negotiations leading to the construction of

new knowledge (Jonassen et al. 2003). These attributes are

not mutually exclusive and reviewers selected as many

attributes as were evident in the lesson (Morrison et al.

2007; Wiggins 1990). PK was also represented by the

assessment methods articulated in the lesson plan. Re-

viewers retrieved this information from the assessment

section of the lesson plan only.

Content Knowledge

CK was retrieved from the objectives and standards sec-

tions of the lesson plan and not inferred from other areas of

the lesson plan. The list of science topics came from

Florida’s Next Generation Sunshine State Standards

(FDLOE 2010).

Technological Pedagogical Knowledge

Technological pedagogical knowledge (TPK) was repre-

sented using the five-level continuum for technology inte-

gration initially developed during the Apple Classrooms of

Tomorrow (ACOT) study (Sandholtz et al. 1996). These

five levels were (a) entry, (b) adoption, (c) adaptation,

(d) infusion, and (e) transformation. The level of

Table 1 Coding criteria in TPACK framework

TPACK construct Review criteria Supporting literature

Content knowledge (CK) Science topics FLDOE (2010)

Pedagogical knowledge (PK) Attributes of meaningful learning

environments, and assessment practices

Jonassen et al. (2003), Morrison et al. (2007),

Wiggins (1990)

Pedagogical content knowledge (PCK) Science practices & cognitive demand for

content area learning

Michaels et al. (2008), Silver et al. (2009)

Technological pedagogical knowledge

(TPK)

Level of integration Sanholtz et al. (1997)

Technological knowledge (TK) General hardware & software Hogarty et al. (2003), Lowther and Ross (2001)

Technological content knowledge (TCK) Science software Kersaint (2003)

Table 2 Software tools in

lesson plansSoftware Pre-lessons (%) Post-lessons (%) v2 p value

Internet browser 45.75 63.93 16.228 0.0001

Presentation 34.64 42.92 3.368 0.0665

Web 2.0 tools 5.56 20.09 24.843 \0.0001

Digital video software 9.80 17.81 6.49 0.0108

Word processing/desktop publishing 8.82 9.59 0.022 0.8821

Digital audio software 7.19 7.76 0.0059 0.9388

Digital imaging software 2.29 7.31 6.523 0.0106

Other 1.63 5.02 3.888 0.0486

Testing software 2.29 4.57 1.451 0.2283

Communication tools 0.65 3.65 4.656 0.031

Spreadsheet 7.84 2.74 5.253 0.0219

Concept mapping 2.61 1.83 0.0862 0.7691

Online textbooks 0.33 1.83 1.656 0.1981

Database 0.33 1.37 0.708 0.4002

Draw/paint/graphics 0.33 0.91 0.0796 0.7779

Authoring 0.98 0.91 0.14 0.708

Digital animation 0.00 0.46 0.0311 0.8601

CD reference 0.65 0.46 0.0915 0.7623

Planning 0.00 0.00 – –

Programming 0.00 0.00 – –

652 J Sci Educ Technol (2015) 24:648–662

123

technology integration was determined using descriptions

from the Technology Integration Matrix, a nationally rec-

ognized tool for identifying technology integration prac-

tices (Allsopp et al. 2007). For example, the following

technology integration descriptors show how entry and

transformational levels were defined in the manual created

for reviewers (Dawson et al. 2011). Details about the re-

viewer training are discussed later.

Entry Level: Typically the teacher uses technology to

deliver curriculum content to students. Entry level

activities may include listening to or watching con-

tent delivered through technology or working on ac-

tivities designed to build fluency with basic facts or

skills, such as drill-and-practice exercises. In a lesson

that includes technology use at the Entry level, the

students may not have direct access to the technology

they may use technology with no stated purpose (i.e.,

taking digital pictures but not doing anything with

them). Decisions about how and when to use tech-

nology tools as well as which tools to use are made

by the teacher. Students solving problems or ma-

nipulating items on an interactive whiteboard usually

occur at this level as well.

Transformational Level: Students use technology

tools flexibly to achieve specific learning outcomes.

They are encouraged to use technology tools in un-

conventional ways and are self-directed in combining

the use of various tools. The teacher serves as a

guide, mentor, and model in the use of technology. A

key distinguishing feature between Infusion and

Transformation is that technology tools are often used

to facilitate higher order learning activities that would

not otherwise have been possible, or would have been

difficult to accomplish without the use of technology.

Pedagogical Content Knowledge

Pedagogical content knowledge (PCK) was represented by

the cognitive demand of the lesson in terms of content area

learning. Cognitive demand is the kind and level of

thinking required of students during a learning experience.

Criteria for low- and high-demand tasks aligned with an-

other study using lesson plans as proxies for teacher

practices (Silver et al. 2009). Low-demand tasks were

identified as those involving skills such as recalling, re-

membering, or applying facts/procedures, while high-de-

mand tasks were identified as those involving skills such as

analyzing, creating, evaluating, and being metacognitive.

Pedagogical content knowledge (PCK) was also repre-

sented by the science practices articulated in the lesson plan.

These science practices were based on the following

practices often associated with inquiry-based science: Les-

son involves a scientifically oriented question or problem;

students collect evidence; students make claims; and stu-

dents engage in reasoning (Michaels et al. 2008; NRC 2000).

Technological Content Knowledge

Technological content knowledge (TCK) was represented

by the content-specific software included in the lesson plan

with reference to its usage by both teacher and students.

Inputs from previous work with math-specific content

specialists (Kersaint 2003) and science educators on the

research team resulted in a list of TCK software. These

include function probe, virtual fieldtrips, and simulations.

Procedures

A cohort of trained reviewers analyzed the lesson plans in

four dyads. A dyad consisted of a science education doc-

toral student and an educational technology doctoral stu-

dent. The reviewers were at various points in their doctoral

studies and had an average of over 6 years of experience

teaching in K-12 environments.

All reviewers attended a 6-h training session conducted

by members of the research team. The training session

served several purposes. First, it allowed the reviewers to

be introduced to each other and the project in a formal

setting and allowed the reviewers to select their dyad

partner based on scheduling preferences. Second, the

training session allowed the research team to formally

prepare the reviewers to identify teacher practices in the

lesson plans following a 14-page manual that was also

developed by the research team. Third, during the training

session, the research team collected data for calculating the

inter-rater agreement across the dyads.

The reviewer training was executed in three iterations

using a gradual release of responsibility model (Pearson

and Gallagher 1983) in which strong scaffolds were

steadily decreased to the point at which reviewers were

independently analyzing the lesson plans. These iterations

were: (a) independent staged walkthrough, (b) dyad staged

walkthrough, and (c) coding simulation. During each stage,

the reviewers either independently or in their dyads re-

viewed a variety of lesson plans that were previously coded

using the manual by members of the research team to

provide a level of consistency in the coding procedures.

Finally, the reviewers were provided a sample of five

science lesson plans drawn from the population lesson plans.

The dyads reviewed all five of the lesson plans indepen-

dently. Inter-rater agreement was calculated for each item,

and scoring differences for inter-rater agreement below

80 % were resolved through dialogue among reviewers and

researchers. The cumulative inter-rater agreement for the

J Sci Educ Technol (2015) 24:648–662 653

123

dyads was 0.94. The dyads coded each lesson plan within

3 weeks of the training session. Reviewers used a web-based

system with a hyperlink to each lesson plan and a rubric with

the codes to identify teacher practices within the lessons.

Each dyad received no more than 130 lessons to review, and

reviewers were compensated for their time.

Data Analysis

Data from the online rubric were exported into IBM SPSS

Statistics 19. Descriptive statistics analysis was conducted

including percentages such as the percentage of science

topics. The percentage of certain level of technology in-

tegration and the percentage of specific technologies uti-

lized in the lesson plans were calculated. Chi-square was

used to compare the proportions of different categories

between pre- and post-lesson plans.

Results

While data analysis occurred around the six constructs of

the TPACK framework, we present our findings organized

around the three questions that guided the research: (1) In

what ways do science teachers involved in a yearlong

technology integration initiative enact technological, ped-

agogical and content practices in lessons? (2) In what ways,

if any, do these practices change during a yearlong tech-

nology integration initiative?

Technological Knowledge

Technological knowledge (TK) was represented based on

the generic types of software and hardware (Hogarty et al.

2003; Lowther and Ross 2001) used within the lessons. In

term of software (see Table 2), the most commonly used

software in the lessons was presentation software (i.e., MS

PowerPoint, Keynote) and Internet browsers (i.e., Internet

Explorer, Firefox). Notable increases were detected in the

use of digital video software (v2 = 6.49, p = 0.0108), In-

ternet browsers (v2 = 16.228, p = 0.0001), Web 2.0 tools

(v2 = 24.843, p\ 0.0001), and digital imaging software

(v2 = 6.523, p = 0.0106). Another notable finding was the

significant decrease in the use of spreadsheets (v2 = 5.253,

p = 0.0219) from pre-lesson to post-lesson.

In terms of hardware, Table 3 shows that the most com-

mon tool employed was a computer (including laptops). In

fact, a significant increase was detected from pre-lesson to

post-lesson in the use of computers (v2 = 13.576,

p = 0.0002). Significant increases also were detected in the

use of tablet technologies (v2 = 13.375, p = 0.0003),

classroom response units (v2 = 6.494, p = 0.0108), digital

microscopes (v2 = 9.2, p = 0.0024), data collectors

(v2 = 4.71, p = 0.03), and handheld devices (v2 = 12.973,

p = 0.0003) from pre-lesson to post-lesson. No significant

decreases were detected from pre-lesson to post-lesson.

Technological Content Knowledge

Technological content knowledge (TCK) was manifested

by the types of science-specific software (Kersaint 2003)

employed within the lessons. As shown in Table 4, very

little science-specific software was employed within the

lesson plans with the exception of web-based science re-

sources. All of the categories of science-specific software

were below 35 %. More importantly, no significant chan-

ges were detected from pre-lesson to post-lesson (Table 4).

Table 3 Hardware tools in

lesson plansHardware Pre-lessons (%) Post-lessons (%) v2 p value

Computers (including laptops) 67.97 82.65 13.576 0.0002

Digital camcorder 9.48 12.33 0.809 0.3683

Digital camera 6.54 8.68 0.567 0.4514

Handheld devices/PDAs/cell phones 1.63 8.68 12.973 0.0003

Other 12.42 6.85 3.771 0.0522

Tablet technologies (iPad, tablets) 0.33 5.94 13.375 0.0003

Data collectors/probes/CBL, CBR, MLB 1.96 5.94 4.71 0.03

Interactive whiteboards 5.88 4.57 0.213 0.6443

Digital microscope 0.33 4.57 9.2 0.0024

Classroom response units (clickers) 0.33 3.65 6.494 0.0108

Document cameras 1.63 2.28 0.0457 0.8308

Microphones/headsets 1.96 2.28 0.0032 0.9549

Graphing calculators 0.00 0.00 – –

Networked calculators 0.00 0.00 – –

654 J Sci Educ Technol (2015) 24:648–662

123

Pedagogical Knowledge

Pedagogical knowledge (PK) was documented in two ways

within the lesson plans: (1) the attributes of meaningful

learning environments (Jonassen et al. 2003) and (2) the

assessment practices employed (Morrison et al. 2007;

Wiggins 1990). In terms of the attributes of meaningful

learning environments (see Table 5), most lesson plans were

active as opposed to passive within these data. Further, more

than 60 % of the pre- and post-submissions were construc-

tive in nature, indicating that students were involved with

the creation of some artifact to demonstrate their knowledge,

skills, and dispositions. We observed significant increases in

the frequency of active (v2 = 9.42, p = 0.0021) and con-

structive (v2 = 18.706, p\ 0.0001) characteristics as ex-

hibited within the lessons. The authenticity of the lessons

was the least well-represented characteristic.

With respect to the assessment practices employed

within the lessons, Table 6 shows an extensive variety.

The most common assessment practices were perfor-

mance-based assessments and short response tests, which

include items like multiple-choice, true/false, fill in the

blank, chapter tests, and unit tests. We observed a significant

decrease in the use of extended response tests (v2 = 4.602,

p = 0.0319) from pre-lesson to post-lesson. Further, we

observed a significant increase in the use of performance-

based assessments (v2 = 10.057, p = 0.0015) and rubrics

(v2 = 4.15, p = 0.0416) from pre-submission to post-sub-

mission. There was also a decrease in the use of short re-

sponse tests from pre-submission to post-submission;

however, this change was not statistically significant.

Content Knowledge

Content knowledge (CK) was represented in the lesson plans

via standards and objectives addressed within the lesson

plans themselves. Again, the list of science topics came from

Florida’s Next Generation Sunshine State Standards

(FDLOE 2010). Teachers focused on an array of content in

their lesson plans as illustrated in Table 7. The content most

frequently addressed within the lessons included the

Table 4 Science-specific

software in lesson plansScience software Pre-lessons (%) Post-lessons (%) v2 p value

Web-based science resources 26.14 30.14 0.828 0.3629

Science content via online services 9.48 9.59 0.0118 0.9137

Virtual simulations 8.17 8.22 0.0198 0.888

Science-specific software 1.96 5.48 3.773 0.0521

Science games 1.63 1.37 0.0148 0.9032

Online data sets for explorations 0.33 0.46 0.228 0.6327

Virtual fieldtrips 0.00 0.00 – –

Table 5 Attributes of

meaningful learning

environments

Attribute Pre-lessons (%) Post-lessons (%) v2 p value

Active 93.14 99.09 9.42 0.0021

Constructive 62.42 80.37 18.706 \0.0001

Cooperative 37.91 45.21 2.519 0.1125

Authentic 9.15 13.70 2.246 0.134

Table 6 Assessment practices

in lesson plansAssessment practices Pre-lessons (%) Post-lessons v2 p value

Performance-based assessment 51.96 66.21 10.057 0.0015

Short response tests 40.85 34.25 2.086 0.1486

Rubrics 20.26 28.31 4.15 0.0416

Extended response tests 15.36 8.68 4.592 0.0321

Teacher observation 11.11 6.85 2.257 0.133

Peer assessment 1.96 2.28 0.0032 0.9549

Group assessment 2.61 1.83 0.0862 0.7691

Student self-assessment 0.65 1.37 0.146 0.7022

No assessment practices specified 0.65 0.00 0.226 0.6348

J Sci Educ Technol (2015) 24:648–662 655

123

following lesson topics as stipulated in the state’s science

standards: the practice of science, matter, interdependence,

organization and development of living organisms, and en-

ergy. We observed a significant increase in organization and

development of living organisms (v2 = 4.535, p = 0.0332)

and interdependence (v2 = 5.663, p = 0.0173) from pre-

submission to post-submission.

Technological Pedagogical Knowledge

Technological pedagogical knowledge (TPK) was repre-

sented using the five-level continuum for technology inte-

gration (Sandholtz et al. 1996): entry, adoption, adaptation,

infusion, and transformation. As shown in Table 8, more

than 95 % of the lesson plans were found on the first three

levels of the ACOT continuum: entry, adoption, and adap-

tation. However, there were significant differences detected

from pre-lesson to post-lesson. In particular, we observed a

significant decrease in the entry-level lesson plans

(v2 = 18.903, p = 0.0003) from pre-submission to post-

submission. Conversely, we observed a significant increase

in the adaptation lesson plans (v2 = 30.258, p\ 0.0001)

and infusion lesson plans (v2 = 5.213, p = 0.0224).

Pedagogical Content Knowledge

Pedagogical content knowledge (PCK) was revealed in two

ways within the lesson plans: (1) science practices

(Michaels et al. 2008) and (2) cognitive demand for content

area learning (Silver et al. 2009). Science practices aligned

to inquiry-based teaching methods as shown in Table 9.

During the post-lessons, students engaged in collecting

data or evidence and making claims at comparable levels.

A notable positive trend was observed in students engaging

in reasoning within the lessons; however, this change was

not statistically significant.

Cognitive demand for content area learning was classified

as either high demand or low demand based on a previous

study (Silver et al. 2009). As can be gleaned in Table 10,

most lesson plans were classified as low-cognitive demand,

meaning the tasks required students to recall, define,

remember, implement, or apply facts to science. However,

we did observe a significant increase in the proportion of

lessons exhibiting a high-cognitive demand (v2 = 10.126,

p = 0.0015) from pre-lesson to post-lesson, meaning stu-

dents more frequently had to justify, compare, assess, ana-

lyze, or evaluate facts related to mathematics or science

Table 7 Science topics in lesson plans

Science topics Pre-lessons (%) Post-lessons (%) v2 p value

The practice of science 21.57 20.09 0.0913 0.7626

Interdependence 12.09 20.09 5.663 0.0173

Organization and development of living organisms 9.80 16.44 4.535 0.0332

Matter 16.99 15.07 0.22 0.6392

Energy 12.09 10.96 0.0678 0.7946

Diversity and evolution of living organisms 5.88 10.05 2.589 0.1076

Heredity and reproduction 6.21 9.13 1.187 0.276

Earth in space and time 6.21 8.68 0.821 0.3649

Earth systems and patterns 6.21 8.22 0.51 0.475

Earth structures 7.19 6.39 0.0333 0.8552

The characteristics of scientific knowledge 6.21 5.94 0.0033 0.9542

Science and society 2.29 4.57 1.451 0.2283

Motion 6.86 4.11 1.318 0.251

Matter and energy transformations 3.92 3.65 0.0052 0.9427

The role of theories, laws, hypotheses, and models 1.63 1.83 0.0279 0.8674

Table 8 Level of Integration

(ACOT continuum) in lesson

plans

Level of integration Pre-lessons (%) Post-lessons (%) v2 p value

Adaptation 28.43 52.51 30.258 \0.0001

Adoption 21.90 26.48 12.34 0.2666

Entry 26.80 10.96 18.903 \0.0001

Infusion 0.33 3.20 5.213 0.0224

Transformation 0.33 0.00 0.0253 0.8736

656 J Sci Educ Technol (2015) 24:648–662

123

content areas. Conversely, a significant decrease in the les-

sons that exhibited a low-cognitive demand (v2 = 5.45,

p = 0.0196) from pre-lesson to post-lesson was detected.

Discussion

In this study, we used TPACK as a theoretical lens to

examine how teachers integrated educational technology as

evidenced through their science lesson plans submitted at

the beginning and end of a one-year technology integration

effort. Though our results show an increase in the overall

sophistication of technologies used, the use of reform-

based science practices was not observed as frequently in

the lesson plans. In the following sections, we discuss our

findings in detail.

Technological Knowledge

Educators agree that when educational technology is suc-

cessfully integrated into teaching, students become en-

gaged with tools that afford them opportunities to analyze

and manipulate systems and processes in the construction

of science knowledge and in problem solving (Hew and

Brush 2007; Neiss 2005). A variety of technologies both

hardware and software tools are easily accessible to many

students. Thus, students enter the science learning envi-

ronment with much familiarity and technological knowl-

edge about the uses and applicability of computers and

related current hardware and software. In this study, TK

was represented by both generic software and hardware.

Teachers used Internet browser software and computers in

their lessons. While these were the most common educa-

tional technology tools, there were significant increases in

other devices such as digital microscopes, tablets, and

handheld devices from pre- to post-lesson plan submis-

sions. We suspect the use of more sophisticated devices

was related to new technologies purchased through the

initiative. Mobile computing devices such as tablet and

handheld devices were the most commonly purchased

items, while probe and peripherals were purchased in large

quantities across the projects (Dawson et al. 2012).

The findings from teachers’ use of the hardware were

complementary to the general software with levels of in-

crease from pre- to post-lessons. Many of the lesson plans

required students to seek information on the Internet and,

in developing their presentation, employed such tools as

digital video and imaging software. However, we were

alarmed at the significant decrease in the use of spread-

sheets from pre- to post-lessons. Spreadsheets have much

utility in inquiry-based science teaching and learning in

constructing graphs and tables, and in analyzing large

amount of data—an important science practice in the use of

evidence to support conclusions.

Pedagogical Knowledge

Attributes of Meaningful Learning

Teachers have the authority to plan and teach what they

deem as necessary for students’ learning. Yet, too often,

high-stakes tests with their punitive consequences are the

deciding factor on what is taught. In support, Haney and

McArthur (2002) posited that the choice of instructional

strategies is influenced by constraints such as adherence to

the local curriculum and high-stakes testing. As a result,

much of K-12 science teaching still revolves around tra-

ditional science teaching dominated by reading compre-

hension and a search for science as a body of knowledge.

Such curricular constraints do affect instructional decisions

and ultimately students’ learning of science.

Research and development in science education and an

understanding of how learning occurs all point to the need

for learners to be actively engaged in science practices

supported by educational technologies and communication

among peers (Michaels et al. 2008). The teachers’ lesson

Table 9 Science practices in

lesson plansScience practices Pre-lessons (%) Post-lessons (%) v2 p value

Students collect data/evidence 39.87 46.12 1.793 0.1806

Students make claims 37.91 42.47 0.926 0.336

Scientifically oriented question or problem 30.39 37.44 2.547 0.1105

Students engage in reasoning 13.07 19.63 3.649 0.0561

Table 10 Cognitive demand for content area learning in lesson plans

Cognitive demand Pre-lessons (%) Post-lessons (%) v2 p value

Low-cognitive demand 68.30 57.99 5.45 0.0196

High-cognitive demand 27.45 41.10 10.126 0.0015

J Sci Educ Technol (2015) 24:648–662 657

123

plans revealed significant increase in both active and con-

structive attributes of a meaningful learning environment

and sought to engage students in strategies that included

manipulation and required the creation and production of

artifacts supporting students’ learning. We posit that the

significant increase in the frequency of both active and

constructive characteristics could be attributed to the

yearlong technology integration initiative. The initiative

offered support in educational technology and may have

fostered the teachers’ realization of the role of these tools

in facilitating the active engagement of students in learning

science. That is, during science instruction, these tools

presented opportunities for students to access science

content knowledge during web-based research.

Authentic, real-world learning experiences and coop-

erative learning environments are important for science

learning. This certainly is consistent with how scientists do

science as advocated by science education reform efforts.

However, the authentic and cooperative attributes were not

well represented in the lesson plans. One plausible expla-

nation is that teachers possibly viewed authentic as related

to immediate, hands-on, in-class activities and not related

to the wide range of real-time science data and other ex-

periences accessible through the use of computer tech-

nology. A lack of such inclusion possibly indicates a lack

of experience or failure on the part of the teachers to rec-

ognize the possibilities of accessing real-world data and

exemplars from sites such as the National Oceanic and

Atmospheric Administration (NOAA), National Aeronau-

tics and Space Administration (NASA), and others. In

addition, we concluded also that the support offered by the

availability of more educational technologies resulted in

the teachers’ planning for individual student access and use

of the devices. Thus, with increasing availability of com-

puters and other educational technologies, the cooperative

attribute of a meaningful learning environment was not

promoted as indicated in the findings.

Assessment Practices

Assessment as a tool to gather information about teaching

and learning is important in learning environments. Current

lesson planning and curricular processes are guided by

students’ responses to formative assessment prompts, while

summative assessment tasks indicate the extent to which

learning in relation to deliberate objectives has been

achieved. In general, lesson plans usually reveal assess-

ment opportunities to determine the extent to which

learning has occurred. The teachers’ pre- and post-sub-

mission lesson plans included a range of common assess-

ment practices requiring both teacher and student

involvement. Noticeably, however, were the significant

increases in both performance-based assessment and the

use of rubrics and the decrease in the use of extended

response tests. We suspect that these practices as repre-

sented in the pre- and post-lesson plans were related to

each other and to the infusion of technology.

Content Knowledge

Science teaching in Florida is mostly guided by the science

topics indicated in the state’s science standards (FLDOE

2010). However, on the national level, standards are not

mandates (NRC 2000) but represent the minimum students

should learn within grade-level bands in public school.

Such guidance is particularly important in a time when

there is a national reform effort to improve students’ sci-

ence learning and embrace science as a cornerstone in

twenty-first century education. Both state and national

standards stress the notion that science teaching and

learning should be consistent with how scientists do sci-

ence. The national standards therefore state the following:

Scientific inquiry refers to the diverse ways in which

scientists study the natural world and propose ex-

planations based on the evidence derived from their

work. Inquiry also refers to the activities of students

in which they develop knowledge and understanding

of scientific ideas, as well as an understanding of how

scientists study the natural world (NRC 2006, p. 23).

This emphasis on inquiry as practice and as a way of

understanding the world has implications for the integration

of classroom strategies that can support effective science

learning. An examination of the frequency of the science

content knowledge topics that emerged in the teachers’ pre-

and post-lesson plan submissions was revealing. The three

content knowledge topics that occurred most frequently—

the practice of science, matter, and energy—are considered

major themes across science disciplinary areas related to

biology, chemistry, and physics. One plausible reason for

the observed frequency of the practice of science could be

attributed to the focus on inquiry-based science (NRC, 1996)

and current efforts to involve learners in science practices

(Michaels et al. 2008). Ironically, other content knowledge

topics related to the nature of science (characteristics of

scientific knowledge and the role of theories, laws, hy-

potheses, and models) did not incur the level of frequency as

the practice of science. This might suggest that teachers

were more comfortable with or more inclined to treat the

practice of science in a generic manner with less emphasis

on the specific related content knowledge of characteristics

of science knowledge, role of theories, laws, hypotheses, and

models. This finding signaled the need for research to ex-

plore how science teachers’ understandings of the tenets of

the nature of science impact their decisions on choice of

science content knowledge topics.

658 J Sci Educ Technol (2015) 24:648–662

123

Only two content topics emerged with significant in-

creases in their representation in the lesson plans from pre-

to post-submission. These biological science topics were

organization and development of living organisms, and

interdependence. This finding might be interpreted in re-

lation to the recent high school graduation requirement and

also is reflective of the time teachers were required to

submit their lesson plans. Students in Florida are required

to pass the state-mandated end-of-course biology ex-

amination. While this finding might suggest a delay in

teaching the topic until closer to the examination date

where students are more likely to exhibit greater perfor-

mance, it also indicates weaknesses in the planned treat-

ment and delivery of science content.

Technological Pedagogical Knowledge

In our exploration of TPK, we embraced the notion that

technology integration may take many forms and is usually

captured along a variety of continuums (Hooper and Rieber

1995; Itzkan 1994; Knenek and Christensen 2000). Fur-

thermore, multiple levels of integration from entry through

to transformation can be observed in any one lesson. More

than 95 % of the lesson plans ascribed to the first three

levels of the ACOT continuum; thus, only 5 % of the

lessons sought to allow students autonomous use of the

technology. We observed a significant decrease in the

frequency of plans that were at the entry levels from pre- to

post-lessons indicating a reduction in the teachers’ use of

technology to deliver science information. At the same

time, there was a significant increase in adaptation lessons

in which teachers incorporated technology tools as integral

components in the development of lesson plans. While

many of these lessons involved students’ independent use

of the technology tools to create particular digital projects,

the lessons lacked students’ use at the infusion and trans-

formative levels. That is, teachers were limited in the ways

they planned to use technology in affording variety and in

supporting the development and use of higher-level skills.

Pedagogical Content Knowledge

Inquiry-Based Science Teaching

Within the category of PCK is the consideration of how

science content knowledge is formulated in ways that are

accessible for learners. While there is no one single pow-

erful representation (Shulman 1986) of science content

knowledge, lesson plans should at least include the teach-

ers’ intent for developing such knowledge. This intent

should include strategies or approaches for shaping and

reshaping students’ understanding of the proposed science

content knowledge and practices per the curriculum.

Furthermore, the plan of action should be derived from the

wisdom of the teachers’ own practices or from knowledge

garnered in previous methods courses or professional de-

velopment experiences.

The focus of the one-year technology integration ini-

tiative was to provide support for integrating educational

technology in science classrooms. On the national level,

inquiry-based science teaching is given much priority in

science curriculum as a way of allowing learners to expe-

rience how scientists do science and science knowledge is

developed (NRC 1996). Inquiry-based science instruction

has also been recommended as a way for teachers to pro-

mote student understanding of the nature of science

(Bianchini and Colburn 2000; Forbes and Davis 2010)

combining science practices, student-designed explo-

rations, and experimentation within the context of the

state’s curriculum.

Science educators contend that engagement in these sci-

ence practices over time will lead to a more scientifically

literate population with a greater appreciation and under-

standing of the nature of science. Our analysis revealed a fair

consistency in how teachers planned to involve students in

scientifically oriented questions, collect data, make claims

substantiated by the evidence collected, and engage in sci-

entific reasoning. Each of these essential features was in-

cluded in the pre- and post-lesson plans. This consistency

could be attributed to the fact that although the focus of the

one-year initiative was on technology integration, little or no

emphasis was placed on PCK within the construct of in-

quiry-based lessons. A plausible explanation for the change

in student reasoning though statistically insignificant could

be that while the other features of inquiry require levels of

individual student engagement, teachers may plan to involve

students in other activities such as structured small- and

whole-group discussions and, with the use of question

prompts, provide opportunities for reasoning and the pos-

sibility of deepening students’ learning.

Cognitive Demand

We embraced cognitive demand as the kind and level of

thinking required of students during a learning experience.

As a critical feature of ensuring depth of understanding,

Silver et al. (2009) described low-demand tasks as those

relating to recall of information such as facts and proce-

dures. For these authors, high-demand tasks included skills

such as analyzing, evaluating, and being metacognitive in

nature. Our findings of high incidences of low-cognitive

demand in both pre- and post-lesson plan submissions

support much of the criticisms directed at science teaching

and facilitated by the nature of high-stakes tests. Too often,

these tests—tied to teachers and school accountability

processes—favor the recall of snippets of science

J Sci Educ Technol (2015) 24:648–662 659

123

information. Similarly, teachers may not have had the

knowledge or experience to use technology to support

higher levels of cognitive demand. Further, technology is

often used as a tool for students to present information,

recite procedures, or memorize facts. While there was a

significant decrease in the low-cognitive demand between

pre- and post-test lesson plans, if the reform efforts of

science teaching are to be realized, there is still the need for

lessons to incorporate more of the skills consistent with

high-cognitive demand.

Technological Content Knowledge

We found a paucity of science-specific software in the

lesson plans. Two possible reasons for this deficiency could

be a lack of awareness of the existence of this type of

software among the teachers. We suspected that during the

year, more emphasis was placed on generic educational

technology hardware tools and software than science-

specific software. Furthermore, teachers seemed unaware

of the great science teaching potentials that exist in uti-

lizing this type of software or in accessing Web sites such

as NOAA and NASA.

Implications

This study was one component of a large Florida tech-

nology integration initiative. Our analysis of pre- and post-

lesson plans identified and documented teachers’ practices

with educational technologies. The implementation of the

initiative offered no guarantee that teachers were posi-

tioned to interpret the goals as intended by policymakers

(Brown and Campione 1996). The findings, therefore, can

be attributed to the extent to which lead administrators and

teachers understood and translated the goals into practice.

A number of misalignments occurred between the goals

of the technology integration initiative and teachers’ in-

tended practices as documented in their lesson plans. In an

era of loud calls for reforms in science teaching, our study

revealed deficiencies in science technological, pedagogical,

and content knowledge and practices in the pre- and post-

lesson plans. We recognized that a gap existed between the

goals of the state’s initiative and the actual implementation

by teachers. According to Lincoln and Guba (1986), this

difference between the stated goals of the initiative and

actual implementation may be attributed to the fact that

interpretation of policies is usually dependent on the lens

through which the policies are viewed. The policy inter-

pretation became a major weakness in the technology in-

tegration initiative, as it did not have a commonly

expressed framework guiding the activities of the stake-

holders involved such as policymakers, district personnel,

and teachers. We posit that TPACK may be a useful

framework to use when educational technology policy

initiatives are to be implemented.

Our findings revealed the occurrence of more positive

and frequent changes in technology practices than science

pedagogical and content practices. Notably, the initiative

provided teachers with technology tools, which could ac-

count for the increases in areas such as general software

and hardware. There is a risk, however, that schools may

invest in an abundance of new technologies faster than the

teachers’ readiness for effective integration to promote

science learning.

Advances in educational technology—focused on inquiry-

based science reform efforts and refinement in instructional

practices—all present challenges and opportunities for sci-

ence teaching. It follows that a one-year initiative with a

focus on technology integration may not have done enough

to engage teachers in related pedagogical and content pro-

fessional development experiences to afford the necessary

change in science teaching practices. Morrison et al. (2007),

in giving credence to collaboration among content fields in

professional development, suggested that the inclusion of

content experts in design and implementation in much the

same way subject area experts are engaged with instructional

design teams. To further effect changes in science pedago-

gical and content knowledge, we offer that science teachers

should be explicitly engaged in content-specific technology

integration efforts simultaneously conducted by the team of

experts from the other related fields. This shared experience

would aptly fit at the intersection of science pedagogical

knowledge, content knowledge, and education technology. In

such a structure, TPACK becomes a viable framework for

technology integration into science lessons.

References

Allsopp MM, Hohlfeld T, Kemker K (2007) The technology

integration matrix: the development and field-test of an internet

based multi-media assessment tool for the implementation of

instructional technology in the classroom. Paper Presented at the

Florida Educational Research Association, Tampa

American Association for the Advancement of Science (AAAS)

(1989) Project 2061: Science for All Americans

American Association for the Advancement of Science (AAAS)

(1993) Benchmarks for science literacy. http://www.project2061.

org/

Archambault LM, Barnett JH (2010) Revisiting technological

pedagogical content knowledge: exploring the TPACK frame-

work. Comput Educ 55(4):1656–1662

Archambault L, Crippen K (2009) Examining TPACK among K-12

online distance educators in the united states. Contemp Issue

Tech Teach Educ 9(1):71

Bianchini J, Colburn A (2000) Teaching the nature of science through

inquiry to prospective elementary teachers: a tale of two

researchers. J Res Sci Teach 37(2):177–209

660 J Sci Educ Technol (2015) 24:648–662

123

Blumenfeld PC, Fishman BJ, Krajcik JS, Marx RW (2000) Creating

usable innovations in systemic reform: scaling up technology-

embedded project-based science in urban schools. Educ Psychol

35(3):149–164

Brantley-Dias L, Ertmer PA (2013) Goldilocks and TPACK: is the

construct ‘‘Just Right?’’. J Res Technol Educ 46(2), 103–128

Brown SD (1998) Twelve middle-school teachers’ planning. Elem

Sch J 89(1):69–87

Brown AL, Campione JC (1996) Psychological theory and the design

of innovative learning environments: on procedures, principles

and systems. In: Schauble L, Glaser R (eds) Innovations in

learning: new environments for education. Erbaulm, Hillsdale,

pp 289–325

Darling-Hammond LL (2000) How teacher education matters.

J Teach Educ 51(3):166–173

Darling-Hammond LL (2010) Evaluating teacher effectiveness: How

teacher performance assessments can measure and improve

teaching. Washington, D.C.: Center for American Progress

Dawson K, Ritzhaupt A, Pringle R, Kersaint G (2011) Manual for

EETT lesson plan reviewers. Unpublished document,

Gainesville

Dawson K, Drexler W, Ritzhaupt AD, Liu F, Barron A, Kersaint G,

Cavanaugh C, Harmes C, Welsh J (2012) Charting a course for

the digital science, technology, engineering, and mathematics

(STEM) classroom interim research and evaluation report. Final

report to the Florida Department of Education. Title II-D/

Enhancing Education Through Technology (EETT) grant

program

Florida Department of Education (2010) Florida next generation

sunshine state standards. FLDOE, Tallahassee

Forbes CT, Davis EA (2010) Curriculum design for inquiry:

preservice elementary teachers’ mobilization and adaptation of

science curriculum materials. J Res Sci Teach 47(7):820–839

Guzey SS, Roehrig GH (2009) Teaching science with technology: case

studies of science teachers’ development of technology, pedagogy,

and content knowledge. Contemp Issues Technol Teach Educ 9(1).

http://www.citejournal.org/vol9/iss1/science/article1.cfm

Haney J, McArthur J (2002) Four case studies of prospective science

teachers’ beliefs concerning constructivist teaching practices. Sci

Educ 86:783–802

Hew KF, Brush T (2007) Integrating technology into K-12 teaching

and learning: current knowledge gaps and recommendations for

future research. Educ Tech Res Dev 55(3):223–252

Hogarty KY, Lang TR, Kromrey JD (2003) Another look at

technology use in classrooms: the development and validation

of an instrument to measure teachers’ perceptions. Educ Psychol

Meas 63(1):137–160

Hooper S, Rieber LP (1995) Teaching with technology. In: Ornstein

A (ed) Teaching: theory into practice. Allyn & Bacon, Neeham

Heights, pp 154–170

Hug B, Krajcik JS, Marx RW (2005) Using innovative technologies to

promote learning and engagement in an urban science classroom.

Urban Educ 40(4):446–472

Itzkan S (1994) Assessing the future of telecomputing environments:

implications for instruction and administration. Comput Teach

4(22):60–64

Jacobs CL, Martin SN, Otieno TC (2008) A science lesson plan

analysis instrument for formative and summative program

evaluation of a teacher education program. Sci Educ

92(6):1096–1126. doi:10.1002/sce.20277

Jonassen D, Howland J, Moore J, Marra R (2003) Learning to solve

problems with technology: a constructivist perspective, 2nd edn.

Merrill Prentice Hall, Upper Saddle River

Kersaint G (2003) Technology beliefs and practices of mathematics

education faculty. J Technol Teach Educ 11(4):549–577

Knenek G, Christensen R (2000) Refining best teaching practices for

technology integration key instructional design strategies

(KIDS). http://www.iittl.unt.edu/KIDS2000/

Koehler MJ, Mishra P (2005) What happens when teachers design

educational technology? The development of technological peda-

gogical content knowledge. J Educ Comput Res 32(2):131–152

Lei J (2007) Technology uses and student achievement: a longitudinal

study. Comput Educ 49(2):284

Lincoln YS, Guba EE (1986) Research, evaluation, and policy

analysis: heuristics for disciplined inquiry. Rev Policy Res

5(3):546–565. doi:10.1111/j.1541-1338.1986.tb00429.x

Lowther DL, Ross SM (2001) Observation of computer use:

reliability analysis. Center for Research in Educational Policy,

The University of Memphis, Memphis

McNeill KL, Pimentel DS (2010) Scientific discourse in three urban

classrooms: the role of the teacher in engaging high school

teachers in high school argumentation. Sci Educ 94:203–229

Michaels S, Shouse AW, Schweingruber HA (2008) Ready, set,

science: putting research to work in K-8 science classrooms.

National Academy, Washington

Mishra P, Koehler MJ (2006) Technological pedagogical content

knowledge: a framework for teacher knowledge. Teach Coll Rec

108(6):1017–1054

Morrison GR, Kemp JE, Ross SM (2007) Designing effective

instruction (5th edn). In: Hoboken NJ (ed), National Education

Technology Plan (2010) Transforming American education:

learning powered by technology, Wiley. http://www.ed.gov/

technology/netp-2010

National Educational Technology Plan (NETP) (2010) Transforming

American education: Learning powered by technology. Wash-

ington, DC. Retrieved from http://www.ed.gov/technology/netp-

2010

National Research Council (1996) National science education stan-

dards. National Academy Press, Washington

National Research Council (2000) Inquiry and the national science

education standards: a guide for teaching and learning. National

Academy, Washington

National Research Council (2006) Research on Future Skill Demands.

Washington, DC.: National Academy Press

Neiss ML (2005) Preparing teachers to teach science and mathematics

with technology: developing a technology pedagogical content

knowledge. Teach Teach Educ 21(5):509–523

Pearson PD, Gallagher MC (1983) The instruction of reading

comprehension. Contemp Educ Psychol 8(3):317–344

Polly D (2011) Examining teachers’ enactment of technological

pedagogical and content knowledge (TPACK) in their

mathematics teaching after technology integration professional

development. J Comput Math Sci Teach 30(1):37–59

Sandholtz JH, Ringstaff C, Dwyer DC (1996) Teaching with

technology: creating student-centered classrooms. Teachers

College Press, New York

Shulman LS (1986) Those who understand: knowledge growth in

teaching. Educ Res 15(2):4–14

Silk Y, Silver D, Amerian S, Nishimura C, Boscardin CK (2009)

Using classroom artifacts to measure the efficacy of professional

development, No. 761. Los Angeles: National Center for

Research on Evaluation, Standards and Student Testing

Silver EA, Mesa VM, Morris KA, Star JR, Benken BM (2009)

Teaching mathematics for understanding: an analysis of lessons

submitted by teachers seeking NBPTS certification. Am Educ

Res J 46(2):501–531

J Sci Educ Technol (2015) 24:648–662 661

123

Slykhuis D, Krall R (2011) Teaching science with technology: a

decade of research. In: Koehler M, Mishra P (eds),Proceedings

of Society for Information Technology & Teacher Education

International Conference 2011). AACE, Chesapeake,

pp 4142–4151. http://www.editlib.org/p/36982

State Educational Technology Directors Association (SETDA) (2011)

national trends. http://www.setda.org/web/guest/2011national

trends. Accessed 15 July 2011

Wiggins, G. (1990). The case for authentic assessment. Practical

Assessment, Research and Evaluation, 2(2). http://PAREonline.

net/getvn.asp?v=2&n=2

662 J Sci Educ Technol (2015) 24:648–662

123