Background

Reading is a critical process in doing, understanding, and using science and mathematics. The ability to make sense of scientific and mathematical texts, with their unique language features, is an important factor that determines student success (Cruz Neri et al., 2021; Ding & Homer, 2020; Yang et al., 2020). Practicing scientists and mathematicians read intensively for their work (Mody, 2015; Shanahan et al., 2011) and reading is an integral part of the discipline’s ways of knowing and epistemic practices. Reading is not a generic ability that is only taught in language arts, but is disciplinary-specific clusters of skills called strategies that require a deep understanding of and engagement with the unique ontological, epistemological, linguistic, semiotic, and pedagogical characteristics of scientific and mathematical language (Yore et al., 2007).

Research in science and mathematics reading has been ongoing for many decades (Borasi & Siegel, 1990; Yore et al., 2003). Currently, there are a number of new developments and contemporary issues that continue to drive the research in this area. One central question that emerges from an increasing understanding of reading is the interconnection among multiple factors that shape reading comprehension, notably readers’ affect and prior knowledge, their language and sociocultural background, linguistic features of different text-types, and other contextual variables. Another current development is a greater awareness and urgency placed on reading (and other language/literacy components) in the disciplines and their connections to scientific and mathematical literacy, as evident in recent curriculum standards such as the Common Core State Standards (CCSS) in the USA and other curricular developments around the world (Tang & Danielsson, 2018). Central to this curricular reform is a shift towards actively changing the educational process, such as developing specific reading strategies and preparing teachers on the role of reading. Furthermore, in today’s digital age, reading is no longer defined by a simple decoding of words in a printed text, but as an engagement with multimodal texts (Kress, 2003). Digital information has greatly changed the way students engage with electronic texts inside and outside the classrooms. It has also expanded student access to information that is not produced and validated by the authorized scientific or mathematical community. This “post-truth” era dominated by social media and fake news requires critical reading of scientific and mathematical matters in terms of their epistemological source, creditability, accuracy, and evidence (Tang, 2021).

Driven by these developments and issues, this special issue set out to invite established and emerging researchers to contribute new knowledge, ideas, and methods. An open call resulted in 38 proposals from researchers in science, mathematics, and language education in 14 countries across five continents. An overview of these proposals indicated that 18 were centered on science, 14 on mathematics, while six focused on both disciplines or science, technology, engineering, and mathematics (STEM) education. Many topics were proposed and they represented the spectrum of issues outlined above (e.g. reading comprehension, linguistic demand, reading strategies, textbook design, teacher education, multimodality, critical literacy). There is also a wide range of methodologies employed in the proposals, with an even spread across quantitative, qualitative, and mixed methods. After the initial selections by the editors and several rounds of external peer review, nine articles (five science education and four mathematics education) were eventually accepted for this special issue, giving an overall acceptance rate of 23.7%.

The papers in this special issue showcase a range of perspectives that inform the authors’ underlying theories/models of reading, literacy, or language. Reading research in science and mathematics education has proliferated and benefited from a diversity of theoretical perspectives. The choice of a perspective (as a lens) tends to foreground or problematize some pertinent issues and render them for systematic investigation, while overlooking other issues (Klette, 2012). Every perspective has its own affordances and limitations. Therefore, a range of perspectives is needed to provide a balanced and holistic understanding of the complexity involved in the field. Careful reading of the articles in this issue reveals four major theoretical perspectives that inform and situate the authors’ work: reading comprehension, scientific/mathematical literacy, disciplinary literacy, and linguistic/semiotic meaning-making. Broadly speaking, these four perspectives roughly correspond to traditions influenced by educational psychology, science/mathematics education research, language and literacy research, and applied linguistics, respectively.

This introductory paper presents the four major perspectives that underpin the authors’ (and many other researchers’) work, followed by a brief introduction of their articles as situated within each of the perspectives. The goal in this endeavor is not to divide the field and the authors’ work into four distinct and mutually exclusive areas, as there are always overlapping boundaries across perspectives and researchers are often influenced by multiple theories. Instead, the purpose of this paper is to map out the theoretical terrain in a way that will help readers navigate the diversity and complexity of reading research and connect the key ideas in the field. This mapping also makes it easier to discern the authors’ contribution to the theory development of reading research in their respective perspectives.

Before discussing the theoretical perspectives, it is pertinent to also point out two recurring cross-perspective themes frequently highlighted or mentioned in most of the articles, regardless of the theories that framed the authors’ work. The first theme is a widespread recognition that scientific and mathematical languages are not confined to just a verbal mode, but are filled with multiple representations such as symbols, equations, images, diagrams, and graphs. Some authors (e.g. Beaudine, 2022; Fazio et al., 2022; Thompson, 2022) explicitly examined this aspect of multimodality in their analysis of reading. Other authors, while predominantly focusing on verbal texts in their analysis, also acknowledged that science and mathematics employ multiple non-verbal resources. As such, it is important to emphasize at the outset that texts are “any representational resources or objects that people intentionally imbue with meaning” (Draper & Broomhead, 2010, p. 28) and that reading—as an engagement with texts—is therefore fundamentally a multimodal endeavor.

The second recurring theme is teacher preparation involving preservice and professional development programs. With a common understanding that science and mathematics teachers are the key to student success in reading science and mathematics, most articles made explicit connections and recommendations to teacher preparation. Several studies focused on teacher education as a subject of study and employed pre- and in-service teachers as research participants (e.g. Cooper et al., 2022; Kwok et al., 2022; Rezat et al., 2022). Other authors drew implications from their findings and made several recommendations concerning teacher education of and collaboration with science and mathematics teachers. These recommendations include explicitly addressing the unique linguistic and multimodal features of science and mathematics texts, modeling the role of reading as a core disciplinary practice in science and mathematics, and developing and teaching disciplinary reading strategies to facilitate student learning.

Major Theoretical Perspectives

Reading Comprehension

Reading is fundamental to science (Norris & Phillips, 2003) and mathematics (Adams, 2003). In school, reading is used frequently as a learning activity that helps students enhance interest and understanding in all subjects, including science and mathematics. For example, through reading science texts, students learn science knowledge, science inquiry, the nature of science, and scientific thinking (Fang & Wei, 2010; Norris & Phillips, 2008; Norris et al., 2009; Phillips & Norris, 2009). Furthermore, when students engage with and learn from text, they get the opportunities to learn the academic and scientific language (Adams, 2003; Fang, 2006) that help them to participate in a science community. Students use mathematics as a language to communicate concepts, solve problems, and engage in academic learning (Shepherd & Van De Sande, 2014). Reading science and mathematics texts are also a critical and reflexive communication process in multimodal ways (Adams, 2003; Alvermann & Wilson, 2011; Karademir & Ulucinar, 2017; Meneses, et al., 2018; Schnotz & Bannert, 2003).

Reading is an active process of meaning-making. Several influential models of reading comprehension conceptualize reading as including both person and text factors, and these may mutually influence each other (e.g. McNamara et al., 2011; Schnotz, 2014; Schnotz & Bannert, 2003). Various reading comprehension component processes contributed differently between scientific and non-scientific genres (Cervetti et al., 2009). Science and mathematics texts contain specialized language forms and functions that challenge students learning. Science and mathematics texts have lots of symbols and technical vocabulary, have high conceptual density, and always use abstract reasoning to explain and argue complex processes and phenomena (Adams, 2003; Fang, 2006; Phillips & Norris, 2009; Shanahan et al., 2011).

The simple view of reading (SVR) is a reading comprehension model consisting of two components—decoding and linguistic comprehension (Hoover & Gough, 1990). Both decoding and linguistic comprehension are interdependently necessary for successful reading. Complemented with the cognitive-processing theories of reading comprehension, the direct and inferential mediational model (DIME model) provides a framework for understanding the dynamics underlying reading comprehension (Cromley & Azevedo, 2007). The DIME model includes five components: background knowledge, word reading, vocabulary, reading strategies, and inferencing, which directly or indirectly influence students’ general reading comprehension across different types of texts. It attempts to integrate components from text processing theories of comprehension (i.e. inference making and reading strategies) which provides a valuable departure from the SVR framework. The models of reading comprehension can point out the influential variables contributing to comprehension and help researchers and teachers understand reading difficulties.

Härtig et al. (2022) used the DIME model of reading comprehension to test general narrative texts as well as science expository texts. This study expanded the reading research emphasis from the English language and text to explore German and text. Seven hundred four German 8th grade students completed measures of comprehension and the DIME predictor variables. Results of two path analyses indicated the general applicability of the model for German and additionally for both genres. The results confirmed the importance of factors including prior knowledge, new vocabulary, inferences from expository texts, and reading strategies on students’ comprehension of science texts.

The linguistic demand of a text might affect reading comprehension. Certain linguistic features, such as complex syntactic structures and low word frequency, have been found to create a higher cognitive load. Hackemann et al. (2022) investigated the influence of linguistic complexity on students’ text comprehension in physics. They considered six interconnected dimensions (structure, conciseness, stimulating additives, simplicity, accuracy, perceptibility) depending on the type of text, its purpose, and readers. Within an experimental study, the researchers measured changes in students’ text comprehension in thermodynamics. The analyses of grades 7–9th students’ responses to multiple-choice comprehension items with three levels of linguistic demands showed that the influence of linguistic complexity on text comprehension was at most low and might be overestimated in science reading literature.

Scientific and Mathematical Literacy

Scientific and mathematical literacies are often defined as an educational goal or vision of what every literate person in science and mathematics should be able to do (Niss & Jablonka, 2014; Roberts & Bybee, 2014). The most common definitions are taken from the Organisation for Economic Co-operation and Development (OECD, 2009, p. 14):

Scientific literacy: An individual’s scientific knowledge and use of that knowledge to identify questions, to acquire new knowledge, to explain scientific phenomena, and to draw evidence-based conclusions about science-related issues, understanding of the characteristic features of science as a form of human knowledge and enquiry, awareness of how science and technology shape our material, intellectual, and cultural environments, and willingness to engage in science-related issues, and with the ideas of science, as a reflective citizen.

Mathematical literacy: An individual’s capacity to identify and understand the role that mathematics plays in the world, to make well-founded judgments, and to use and engage with mathematics in ways that meet the needs of that individual’s life as a constructive, concerned, and reflective citizen.

The OECD’s definitions, along with many researchers (e.g. Niss & Jablonka, 2014; Roberts & Bybee, 2014), emphasize the knowledge, processes, and applications in science and mathematics, but they do not specify what are the key attributes that will enable individuals to achieve those stated goals. Specifically, these definitions lack the literacy component of scientific/mathematical literacy (Yore, 2011).

Norris and Phillips (2003) made a useful distinction between the two different aspects of scientific literacy—the “fundamental sense” as being fluent in the resources of text used in science in order to understand its meaning and the “derived sense” of being knowledgeable in the subject-matter of science. With the central premise that scientific knowledge is largely constituted by texts, they argue that the derived sense of scientific literacy “would not be possible without text and without literacy in the fundamental sense” (p. 233). Some examples of literacy in the fundamental sense include being able to read and critique information related to science from different sources (e.g. news media, medical and food labels, internet sites), produce and communicate knowledge through various forms of literacy (e.g. reading, writing, talking, listening, representing, interpreting), and understand and appreciate science as a particular way of inquiry.

Many science education researchers are also familiar with the two visions of scientific literacy (Roberts, 2007). Vision I focuses on the knowledge and processes of science and vision II focuses on the scientific applications and issues that students will likely engage in society. Taking into consideration the fundamental sense of scientific literacy, Yore (2012) argues the need for a vision III of “Scientific Literacy for All” that integrates the language in science research, nature of science, science teaching and learning, and contemporary science education reforms. Achievement of scientific literacy that leads to fuller participation in public debate on socioscientific issues means vision III is needed to prepare all citizens in developing the “critical knowledge, emotional dispositions, thinking ability, and literacy strategies” to read and engage in science (Yore, 2012, p. 8).

Chen et al.’s (2022) work is well situated in the literature focusing on scientific literacy. Their goal of integrating the history and nature of science (HOS/NOS) into an already crowded science curriculum in Taiwan (focusing on knowledge and skills) is fueled by the importance of vision III of scientific literacy to ensure students have an appreciation of the epistemic underpinnings of science as they read scientific texts. Recognizing that the historical vignettes found in most science textbooks are often ignored by teachers and students, they developed an opportunity to use homework notebook to integrate students’ reading of historical vignettes. Specifically, the Taiwanese schools’ educational practice of integrating reading and writing tasks in homework notebook, instead of using notebook for assignment recording purposes, functioned as a key enabler to accentuate the role of literacy in guiding students’ academic performances and scientific literacy. Chen et al. “echoed the claim of a fundamental sense of scientific literacy and suggests that science reading and writing tasks should be rigorously integrated into regular science lessons, as well as existing reading courses, to foster students’ literacy competences in different learning contexts.”

As for mathematical literacy, this development involves fundamental attributes such as, reading mathematical texts with comprehension and writing and speaking to communicate mathematical ideas. The National Council of Teachers of Mathematics (NCTM, 2013) stipulates mathematical literacy as a key process standard involving reading, writing, and discussing ideas using the language of mathematics. Likewise, the Victorian curriculum for mathematics in Australia emphasizes that reading in the context of mathematics is essential as it supports making meaning (interpretation) and communication of mathematical ideas (Victorian Curriculum and Assessment Authority, n.d.). It is apparent that there is a need for reading to be a part of mathematics instruction at all levels of schooling. As the reading of mathematics involves making sense of mathematical symbols, notations, representations, and mathematical vocabulary, it is not akin to reading a literary text. Thus, it is advocated that reading to learn mathematics be in a transactional manner, where readers are actively making sense of the text read (see Borasi & Siegel, 1990; O’Mara, 1981).

Textbooks are key to mathematics instruction around the world (Valverde et al., 2002). Several researchers have noted that the textbooks teachers adopt for their teaching often result in dictating the content they teach and the teaching strategies they adopt (Freeman & Porter, 1989; Reys et al., 2004). Therefore, it is not surprising that textbooks may be used as proxies to determine students’ opportunity to learn (OTL) (Schmidt et al., 1997; Tornroos, 2005). Though textbooks may have the potential to help students develop an understanding of mathematics, often many students are unable to read and hence use their textbooks effectively as learning tools. Teachers thus need to mediate their students’ use of textbooks (Weinberg & Wiesner, 2011).

Thompson’s (2022) article iterates that reading mathematical texts is an essential component of developing deep mathematical understanding imperative for one’s mathematical literacy. In particular, Thompson researched whether expectations and perceptions about reading might be facilitated by using textbooks in which reading was embedded as a curriculum feature. Overall, teachers and students using a curriculum with reading embedded tended to report more frequent uses of reading than those using a curriculum without such embedded features. Teachers and students in geometry classes typically reported more frequent reading than those in advanced algebra classes, with geometry teachers using textbooks with embedded reading often reading aloud in class and discussing the reading as part of instruction. Teacher concerns related to reading included the readability of the text, the time that reading took during the class when so much content needed to be covered, and the need to model reading strategies for students, particularly at the beginning of the school year. Thompson noted that just embedding reading into the design of the textbooks was not enough to ensure that it was a regular feature of instruction. Teachers need to be cognizant of the role of reading in mathematics instruction so that, with adequate support from curriculum developers in the teacher notes and textbook guides, they may facilitate the development of mathematical literacy among their students.

Disciplinary Literacy

Another perspective with a major impact on reading research in science and mathematics originated from the literacy research community under various banners of “literacy across the curriculum,” “content area literacy,” and more recently, “disciplinary literacy” (Shanahan et al., 2011). With the mantra that “all teachers are literacy teachers,” researchers since the 1960s have argued that reading and writing should also be taught or emphasized in science and mathematics classrooms (Parker, 1985). In the past, reading strategies that are universal across all content areas, such as the popular SQ3R (survey, question, read, recite, review) or CORI (concept-oriented reading instruction), were recommended for science and mathematics teachers to help their students tackle different texts. However, the uptake is low as many content teachers are largely resistant towards these generic non-disciplinary strategies (Moje, 2008).

Disciplinary literacy is a more recent development that moves away from a universal notion of literacy towards a view of literacy as social practices connected to a specific form of language for specific historical, cultural, and institutional contexts (Gee, 2011). Shanahan and Shanahan (2012) argue that while content area literacy focuses on reading or writing texts independent of the subject area, disciplinary literacy “emphasizes the unique tools that the experts in a discipline use to participate in the work of that discipline” (p. 2). Therefore, the emphasis of infusing generalizable reading strategies across all subject areas is gradually replaced by the need to focus on the specialized ways of reading, writing, knowing, and doing within a discipline (Moje, 2007; Shanahan & Shanahan, 2012).

Focusing on the importance of disciplinary expertise, Shanahan et al. (2011) investigated how experts read in three disciplines—mathematics, chemistry, and history, and provided specific examples of disciplinary literacy in those respective content domains. Using think-aloud protocols in an expert-reader study, they found distinctive differences in their reading behaviors, particularly in the area of “sourcing, contextualization, corroboration, close reading and rereading, critical response to text, and use of text structure or arrangement and graphics” (p. 393). For instance, in the area of critique, mathematicians tend to focus on error and correctness of information (internal inconsistency) while chemists focus on corroboration with known scientific evidence (external consistency). Mathematicians often use close reading (and rereading) as a strategy to meticulously weigh the information of every word in order to ensure an accurate understanding of the problems and solutions presented in the text. By contrast, chemists are more selective in their close reading to some portions of a text that require greater attention. The reading of non-verbal representations is integral to both mathematics and chemistry, but there are notable differences in their interpretation. Chemists tend to see graphics as alternative forms of information and are conscious in comparing and translating graphics and written text cognitively back and forth. Mathematicians, on the other hand, do not separate equations and prose as they interpret them together in a unified and linear manner.

Informed by the research from disciplinary literacy, Beaudine (2022) investigated the reading practices of middle school students as they read mathematical texts. Building on existing research that examined expert readers of mathematics (e.g. Shanahan et al., 2011; Shepherd & van de Sande, 2014), they recognized a lingering research gap of identifying commonly used reading strategies by 22 students in the USA. Instead of assuming a deficit model where novices (i.e. students) are lacking of any productive reading strategy, Beaudine sought to identify students’ reading resources as he used a think-aloud protocol to interview the students while they were reading a mathematical passage. The study found the students used a wide range of strategies with six particular strategies used almost universally—read aloud, pause to reflect, plan a solution or predict results, paraphrase text, question or critique the text, and self-check. Beaudine urges mathematics educators to harness known strategies that can support students’ mathematical reading comprehension as well as model effective strategies clearly and consistently in the classroom for students to follow.

Rezat et al. (2022) also started with the position that literacy is disciplinary specific and successful reading of mathematical texts will require specific practices and strategies to navigate complex texts. They found two strands of research in the mathematics education literature related to this area—one focusing on empirical investigations of reading strategies by experts (e.g. Berger, 2019; Shanahan et al., 2011) and the other focusing on pedagogical suggestions to teach close reading of mathematical texts (e.g. Fisher & Frey, 2016). Their unique contribution lies in connecting these two strands of research as they aimed to develop and evaluate instructional materials to scaffold close reading of mathematical text. Using a design research approach with 296 first-year preservice teachers in Germany, these researchers developed several reading-strategy videos, close-reading tasks, and homework tasks and problems to support the preservice teachers in different stages of mathematical reading. The study found that the preservice teachers believed that the close-reading tasks were most beneficial for their learning.

Cooper et al. (2022) shifted the focus of reading practices in this special issue from students and preservice teachers (by Beaudine, 2022; Rezat et al., 2022) to practicing educators. They studied a reading group that aimed to foster professional learning and development among a group of science educators in Australia. They drew on the framework of pedagogical content knowledge (PCK) to investigate how reading can play a role in linking the educators’ personal PCK to the collective PCK, or specialized shared knowledge for teaching particular content to particular students in specific contexts. Although the study was not framed by a theory of reading or literacy, we can draw several connections to disciplinary literacy in terms of how experts read within the discipline of education (and science education more specifically). The study highlights that much of the reading practices of science educators are self-guided reading and well-facilitated discussion within the context of professional learning with fellow educators. Thus, the role of reading and literacy is not only important for science and mathematics learners, but also for the preparation of science and mathematics teachers as well.

Linguistic/Semiotic Meaning-Making

The last theoretical perspective that shapes researchers’ view of reading is rooted in the tradition of examining the linguistic and semiotic patterns of disciplinary texts (Bezemer & Cowan, 2021; Martin & Veel, 1998). Halliday’s (1978) theory of systemic functional linguistics (SFL) and later social semiotics provide a comprehensive framework, analytical apparatus, and metalanguage to analyze language use in different social contexts. With an underlying premise that language is a semiotic resource for making meaning in a social context, instead of just a communicative tool that expresses pre-existing thought (c.f. Vygotsky, 1986), researchers regard language as a fundamental building block for constructing scientific and mathematical knowledge. Therefore, learning science and mathematics will undoubtedly involve learning the unique disciplinary languages involved in reading, writing, listening, and talking science and mathematics (Fang & Schleppegrell, 2010; Lemke, 1990; O'Halloran, 2000).

Researchers using SFL often go beyond identifying surface linguistic features (e.g. passive voice, technical terms) to describe how scientific and mathematical meanings are mediated through language, as well as illustrate how scientific and mathematical knowledge are constructed through a “network of semantic relationships among words and symbols that are shared, institutionalized, and repeatedly constructed on multiple occasions and settings” (Tang, 2020, p. 74). Tang’s (2011) analysis of science and mathematics curriculum documents revealed how several “concept words” (e.g. energy, distillation, addition) are not just technical terms to highlight during instruction (i.e. nominalization; see Fang, 2005), but they are an accumulation of multiple taxonomic and logical relationships consisting of process verbs, hyponyms, meronyms, conjunctions, and everyday objects, as well as a particular assemblage of images, numbers, symbols, and graphs. Similarly, mathematical equations (e.g. KEi  +  PEi  +  Wext  =  KEf  +  PEf) are not just a peculiar form of expression, but they function as symbolic tools to make certain operational, categorical, quantitative, and spatial meanings required in mathematical discourse (Lemke, 2003; O'Halloran, 2000; Tang, 2011).

SFL has a huge influence in the historical development of social semiotics—a “theory about meaning and meaning-making in interaction; it examines the varieties of ways texts can be made” (Gualberto & Kress, 2019, p. 1). Building on Halliday’s (1978) central idea of “language as social semiotic,” several researchers expanded the theoretical framework to investigate the meaning potential of non-verbal semiotic modes, notably in images and mathematical symbolism (e.g. Kress & van Leeuwen, 2006; Lemke, 1998; O'Halloran, 2005). Development in social semiotics signifies a departure from a linguistic-centric view of reading and writing towards a broader view of seeing all meaning-making as multimodal. Researchers are also beginning to develop new models for working with texts to replace previous frameworks that are biased towards written text. One example is Danielsson and Selander’s (2016) model for reading multimodal texts that takes into account the general structure of multimodal text, how different semiotic resources operate and combine, and the use of figurative language and explicit/implicit values, and aims to highlight multimodal text analysis in relation to the subject-area content.

Kwok et al.’s (2022) study exemplifies the theoretical perspective and approach in SFL to analyze mathematical texts. Building on the broad-level descriptions of mathematical discourse (e.g. Fang & Schleppegrell, 2010; O'Halloran, 2000), Kwok et al. analyzed a corpus of 400 word problems in primary school textbooks to reveal the various grammatical patterns of expressing distinct mathematical meanings involved in one-step additive word problems. Their analysis reveals three patterned types of additive word problems that are characterized by the number of referents (quantified units) and their hierarchical relations (e.g. sub-type, part-whole), process types (e.g. action, stasis), time markers (e.g. then, now), and comparative connectors (e.g. more, smaller). Based on these linguistic findings, they then designed an instructional unit for preservice teachers to better analyze and understand the language of word problems. These preservice teachers were introduced to the metalanguage of referents, processes, time markers, and comparative connectors so that they could gain the language precision to identify the mathematical meanings associated with additive word problems and the inherent language challenges posed by those word problems.

Fazio et al. (2022) focused on how adolescent learners engage in critical reading of multimodal texts dealing with socio-scientific issues (SSI). Drawing on social semiotics researchers such as Kress (2010) and Danielsson and Selander (2016), they view science reading and literacy as multimodal meaning-making at large. Specifically, Fazio et al. applied Danielsson and Selander’s (2016) model to design and analyze two multimodal texts read by six Canadian adolescents (age 10–14 years) in terms of the underlying text structures, resources, social, affective, and cognitive dimensions. Think-aloud observational protocol was used to assess the students’ critical thinking as they read one text on climate change, followed by another text with similar content but contrasting viewpoint. Their results suggested several factors that shape readers’ engagement with multimodal texts, including their background knowledge, emotional engagement, cognitive dissonance from contrasting viewpoints, argument competency, and the impact of visual images.

Concluding Remarks

The selection of papers in this issue collectively represents a growing expansion and maturity in the research on science and mathematics reading. The field has ventured beyond a SVR focusing on decoding words, vocabulary instruction, and nonspecific strategies to more sophisticated and nuanced theories that consider the disciplinary, epistemic, and multimodal nature of science and mathematics. The nine papers showcase the diverse range of theoretical perspectives that were developed from decades of research in science and mathematics education, language and literacy education, educational psychology, and applied linguistics. At the same time, the papers also provide insights into the applications of different perspectives to address the contemporary issues that continue to drive the research on reading in science and mathematics.