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Proficiency Scales for the New Science Standards: A Framework for Science Instruction and Assessment

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Transform an in-depth understanding of the new science standards into successful classroom practice. You’ll learn how to align instruction and assessment with the science standards and create proficiency scales that can be used to plan all types of lessons. Discover hundreds of ready-to-use proficiency scales derived from the Next Generation Science Standards that are applicable to specific areas of science instruction.

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1 The Evolution of Standards-Based Education in Science

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In previous decades, educators in the United States called for K–12 science standards that schools could broadly implement across the country. These requests ultimately prompted the development of comprehensive science standards such as the National Research Council’s (NRC; 1996) National Science Education Standards (NSES) and the American Association for the Advancement of Science’s (AAAS) Benchmarks for Science Literacy (1993, 2009). These documents enjoyed extensive use and adaptation throughout the U.S. and often guided the development of individual state science standards (Colorado Department of Education, 2009; Massachusetts Department of Education, 2006; Minnesota Department of Education, 2009; Wyoming State Board of Education, 2008).

However, the NSES and the AAAS Benchmarks were originally published in 1996 and 1993 respectively. In 2010, the release of the widely adopted Common Core State Standards (CCSS) in English language arts (ELA; National Governors Association Center for Best Practices & Council of Chief State School Officers [NGA & CCSSO], 2010a) and mathematics (NGA & CCSSO, 2010b) confirmed that these previous science standards documents needed to be updated. As Achieve (n.d.a) noted, during the fifteen-year period between the publication of both science standards documents and the CCSS, “major advances in science” warranted adjustments to K–12 science instruction. Aside from the demand for an up-to-date curriculum, new science standards were needed for at least four additional reasons.

 

2 Measurement Topics, Proficiency Scales, and the NGSS

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Even a cursory reading of chapter 1 demonstrates that the Next Generation Science Standards (NGSS; NGSS Lead States, 2013) were a remarkable accomplishment—both broad in scope yet deep in rigor. But these laudable characteristics also made them difficult for a busy teacher to implement. This book is intended to help teachers translate content from the NGSS into a format that guides both assessment and instruction through the use of proficiency scales.

In simple terms, a proficiency scale can be thought of as the organization of important content for a specific topic into three levels of difficulty: (1) the target content, (2) the simpler content, and (3) the more complex content. To illustrate, consider the following target content a middle school science teacher might identify as a goal:

The student will analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects.

This represents the desired level of knowledge the teacher would like all students to attain as the result of a specific lesson or set of lessons and is commonly referred to as the target learning goal or simply the learning goal. In this case, the target learning goal is taken directly from the NGSS (more specifically, from performance expectation MS-ESS3-2; see Achieve, 2013a, p. 72).

 

3 Proficiency Scales and Classroom Instruction

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Effective instruction begins with effective planning, and use of a proficiency scale often optimizes the planning process. To illustrate, assume that a middle school teacher is planning instruction for a set of lessons on the measurement topic of Water and Earth’s Surface using the proficiency scale shown in table 3.1.

Table 3.1: Middle School Proficiency Scale for the Measurement Topic of Water and Earth’s Surface

The proficiency scale in table 3.1 is from part II of this book (page 55). As described in chapter 2, the score 3.0 content for each proficiency scale in part II was taken directly from the Next Generation Science Standards’ (NGSS; NGSS Lead States, 2013) performance expectations (though we paraphrased the associated clarification statements in parentheses). Researchers then used the score 3.0 content to inform the score 2.0 content. For planning purposes, however, a teacher might want to augment the scales with additional content. In fact, we strongly recommend that teachers add content or change the language of proficiency scales to tailor them to their own needs. With this in mind, teachers might add the following.

 

4 Proficiency Scales and Classroom Assessment

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In addition to guiding classroom instruction, proficiency scales can also guide classroom assessment. Indeed, educators originally coined the term measurement topic because teachers found that proficiency scales served as useful assessment tools. This is primarily because the process of constructing a proficiency scale is very similar to the process test designers use when constructing an assessment.

While there are many descriptions of the test design process (see Downing & Haladyna, 2006), all share at least two characteristics: (1) specification of content and (2) identification of the content’s level of difficulty. These two features are depicted in table 4.1.

Table 4.1: Identification of Level of Difficulty of Content for Test Design

The content axis (horizontal axis) in table 4.1 identifies measurement topics for assessment. In table 4.1, these subjects include the measurement topics of Inheritance of Traits, Variation of Traits, and Adaptation. The difficulty axis (vertical axis) addresses how easy or hard the content will be. To identify the difficulty level of content, some type of taxonomy is typically used. Webb (2006) suggested the following levels of cognitive complexity: level 1 (recall), which includes the recall of simple information; level 2 (skill/concept), which requires students to make a decision in response to a problem or activity; level 3 (strategic thinking), which requires reasoning, planning, using evidence, or higher-level thinking; and level 4 (extended thinking), which requires higher-level, complex thinking over extended periods of time. However, table 4.1 implements the taxonomy described in tables 2.8 and 2.9 (pages 25–28) and appendix A (page 127).

 

Proficiency Scales for the Next Generation Science Standards

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As mentioned in part I, the proficiency scales created by Marzano Research were designed to include all of the performance expectations from the Next Generation Science Standards (NGSS; Achieve, 2013a). Here we include a brief explanation of performance expectation codes as well as a few notes about the scales.

Performance expectation codes cite the original performance expectation(s) upon which a scale is based. Each code identifies the grade level, discipline, core idea, and performance expectation number of the NGSS performance expectation associated with it.

The grade-level identifications are fairly straightforward. A number indicates a performance expectation’s corresponding grade level (for example, 1 means grade 1), and K, MS, and HS indicate kindergarten, middle school, and high school, respectively.

The following letters indicate to which discipline from the NGSS a performance expectation belongs.

Physical sciences = PS

Life sciences = LS

 

Appendix A: Using the New Taxonomy of Educational Objectives

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The taxonomy presented here is part of a more comprehensive framework titled The New Taxonomy of Educational Objectives (Marzano & Kendall, 2007; see also Marzano & Kendall, 2008). Robert J. Marzano (2009) previously described the relationship between this taxonomy and designing and teaching learning goals and objectives in Designing & Teaching Learning Goals & Objectives.

As described in chapter 2 (page 25), the taxonomy includes four levels.

Level 4 (Knowledge Utilization)

Level 3 (Analysis)

Level 2 (Comprehension)

Level 1 (Retrieval)

To understand the taxonomy as it applies to academic content, it is necessary to address two types of knowledge: (1) declarative knowledge and (2) procedural knowledge. Declarative knowledge is informational content that can be conceptualized as a hierarchy in its own right. At the bottom of the declarative knowledge hierarchy is vocabulary—terms and phrases about which an individual has an accurate but not necessarily deep understanding. Facts reside a level above vocabulary terms and phrases. The highest level of the declarative knowledge hierarchy consists of generalizations, principles, and concepts.

 

Appendix B: Strategies for Setting an Effective Context for Learning

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Noticing When Students Are Not Engaged and Reacting

A teacher notes which students are not engaged and takes overt action to re-engage those students. Specific strategies include scanning the room, monitoring levels of attention, and measuring engagement.

Using Academic Games

A teacher uses inconsequential competition to maintain student engagement. Specific strategies include Classroom Feud, turning questions into games, and vocabulary review games.

Increasing Response Rates

A teacher maintains student engagement by using response-rate techniques during questioning. Specific strategies include response cards, paired or choral response, and elaborative interrogation.

Using Physical Movement

A teacher uses physical movement to keep students engaged. Specific strategies include body representations, drama-related activities, and asking students to stand up and stretch.

 



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